FanqingM
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MMIU-Benchmark
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threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.756, -0.319, 1.042, 0.429, 0.322, 0.448]] B: [[-0.968, 0.035, 0.911, 0.64, 0.607, 0.13]] C: [[-0.447, -0.667, 1.37, -0.048, 0.547, 0.66]] D: [[-0.868, -0.191, 0.853, 0.715, 0.451, 0.897]]
Given a RGB image and a depth image, please detect the 3D bounding box of the coffee maker in the scene. The camera pose information includes: the rotation matrix: [[-0.848489, -0.131122, 0.512712], [-0.527579, 0.133483, -0.838954], [0.041567, -0.982339, -0.182436]]; the translation vector: [2.702568, 1.718074, 1.602473], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.756, -0.319, 1.042, 0.429, 0.322, 0.448]] B: [[-0.968, 0.035, 0.911, 0.64, 0.607, 0.13]] C: [[-0.447, -0.667, 1.37, -0.048, 0.547, 0.66]] D: [[-0.868, -0.191, 0.853, 0.715, 0.451, 0.897]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_102_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_102_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.912, -2.332, 1.905, 0.812, 1.477, 1.176], [1.567, 2.82, 1.32, 0.327, 1.345, 2.178]] B: [[1.7, -2.606, 1.565, 0.678, 1.073, 1.573], [1.645, 3.122, 1.233, 0.724, 1.059, 2.428]] C: [[2.101, -2.524, 1.207, 0.883, 0.819, 1.727], [1.696, 3.351, 1.474, 0.479, 1.235, 2.058]] D: [[1.681, -2.688, 1.507, 0.221, 0.833, 1.776], [1.4, 2.653, 1.693, 1.075, 1.288, 2.071]]
Given a RGB image and a depth image, please detect the 3D bounding box of the cabinet in the scene. The camera pose information includes: the rotation matrix: [[0.606497, 0.359513, -0.709163], [0.793947, -0.321582, 0.515978], [-0.042553, -0.875977, -0.480473]]; the translation vector: [5.898605, 1.464963, 1.329018], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.912, -2.332, 1.905, 0.812, 1.477, 1.176], [1.567, 2.82, 1.32, 0.327, 1.345, 2.178]] B: [[1.7, -2.606, 1.565, 0.678, 1.073, 1.573], [1.645, 3.122, 1.233, 0.724, 1.059, 2.428]] C: [[2.101, -2.524, 1.207, 0.883, 0.819, 1.727], [1.696, 3.351, 1.474, 0.479, 1.235, 2.058]] D: [[1.681, -2.688, 1.507, 0.221, 0.833, 1.776], [1.4, 2.653, 1.693, 1.075, 1.288, 2.071]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_103_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_103_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.693, -1.201, 1.187, 0.828, 0.813, 1.996]] B: [[-1.283, -1.49, 1.157, 1.223, 0.635, 2.337]] C: [[-1.607, -1.608, 0.733, 1.415, 0.912, 2.422]] D: [[-1.367, -1.969, 1.373, 1.253, 1.096, 1.909]]
Given a RGB image and a depth image, please detect the 3D bounding box of the cabinets in the scene. The camera pose information includes: the rotation matrix: [[0.349467, 0.022881, -0.936669], [0.936944, -0.011774, 0.349282], [-0.003037, -0.999669, -0.025553]]; the translation vector: [3.08553, 2.787215, 1.609269], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.693, -1.201, 1.187, 0.828, 0.813, 1.996]] B: [[-1.283, -1.49, 1.157, 1.223, 0.635, 2.337]] C: [[-1.607, -1.608, 0.733, 1.415, 0.912, 2.422]] D: [[-1.367, -1.969, 1.373, 1.253, 1.096, 1.909]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_104_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_104_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.858, -0.632, 0.828, 0.126, 1.643, 1.687], [-1.33, 0.028, 0.915, 0.226, 2.888, 1.864], [-0.174, -1.42, 0.865, 2.224, 0.121, 1.722], [0.61, 1.413, 0.874, 4.003, 0.17, 1.77], [2.563, 1.11, 0.788, 0.118, 0.484, 1.649]] B: [[1.405, -0.208, 0.598, -0.114, 2.093, 1.602], [-1.061, 0.394, 1.019, -0.16, 3.193, 1.369], [-0.359, -0.986, 0.414, 1.802, -0.111, 1.429], [1.035, 1.154, 1.154, 3.812, 0.204, 2.113], [2.12, 1.579, 1.171, -0.054, 0.234, 1.478]] C: [[1.89, -0.153, 0.406, 0.028, 1.816, 1.93], [-1.451, -0.417, 1.393, -0.113, 3.307, 1.683], [-0.295, -1.25, 0.577, 1.985, -0.098, 1.447], [0.348, 1.382, 0.753, 3.885, 0.441, 1.993], [2.183, 0.625, 0.617, 0.117, 0.723, 1.324]] D: [[2.301, -0.62, 1.122, 0.26, 2.124, 2.126], [-0.834, -0.412, 1.071, -0.118, 2.484, 1.498], [-0.094, -1.494, 0.531, 2.098, -0.018, 2.208], [0.226, 1.164, 1.047, 4.422, 0.121, 1.595], [2.644, 1.556, 0.635, 0.354, 0.125, 1.662]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.991592, 0.052224, -0.118397], [0.1292, -0.348306, 0.928435], [0.007248, -0.935925, -0.352124]]; the translation vector: [2.177373, 2.142725, 1.46728], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.858, -0.632, 0.828, 0.126, 1.643, 1.687], [-1.33, 0.028, 0.915, 0.226, 2.888, 1.864], [-0.174, -1.42, 0.865, 2.224, 0.121, 1.722], [0.61, 1.413, 0.874, 4.003, 0.17, 1.77], [2.563, 1.11, 0.788, 0.118, 0.484, 1.649]] B: [[1.405, -0.208, 0.598, -0.114, 2.093, 1.602], [-1.061, 0.394, 1.019, -0.16, 3.193, 1.369], [-0.359, -0.986, 0.414, 1.802, -0.111, 1.429], [1.035, 1.154, 1.154, 3.812, 0.204, 2.113], [2.12, 1.579, 1.171, -0.054, 0.234, 1.478]] C: [[1.89, -0.153, 0.406, 0.028, 1.816, 1.93], [-1.451, -0.417, 1.393, -0.113, 3.307, 1.683], [-0.295, -1.25, 0.577, 1.985, -0.098, 1.447], [0.348, 1.382, 0.753, 3.885, 0.441, 1.993], [2.183, 0.625, 0.617, 0.117, 0.723, 1.324]] D: [[2.301, -0.62, 1.122, 0.26, 2.124, 2.126], [-0.834, -0.412, 1.071, -0.118, 2.484, 1.498], [-0.094, -1.494, 0.531, 2.098, -0.018, 2.208], [0.226, 1.164, 1.047, 4.422, 0.121, 1.595], [2.644, 1.556, 0.635, 0.354, 0.125, 1.662]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_105_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_105_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.401, -1.054, 0.005, 0.193, -0.189, 0.608], [-1.764, -0.727, 0.562, 0.549, 0.36, 0.374], [-2.181, 0.328, -0.167, 0.351, 0.064, 0.119]] B: [[1.152, -0.296, 0.418, 0.864, 0.385, 0.356], [-2.324, -0.32, 0.424, 0.485, 0.66, -0.082], [-1.955, 0.121, 0.148, 0.369, 0.415, 0.131]] C: [[1.282, -0.743, 0.129, 0.493, 0.257, 0.293], [-1.968, -0.763, 0.156, 0.467, 0.241, 0.31], [-1.95, 0.267, 0.16, 0.231, 0.318, 0.302]] D: [[1.109, -0.73, -0.038, 0.564, 0.587, 0.172], [-2.259, -0.589, 0.46, 0.771, -0.144, -0.09], [-1.478, 0.494, 0.535, 0.374, 0.223, 0.643]]
Given a RGB image and a depth image, please detect the 3D bounding box of the trash can in the scene. The camera pose information includes: the rotation matrix: [[-0.789457, 0.162095, -0.592016], [0.613764, 0.197318, -0.764434], [-0.007096, -0.966846, -0.255262]]; the translation vector: [5.114759, 3.17533, 1.386193], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.401, -1.054, 0.005, 0.193, -0.189, 0.608], [-1.764, -0.727, 0.562, 0.549, 0.36, 0.374], [-2.181, 0.328, -0.167, 0.351, 0.064, 0.119]] B: [[1.152, -0.296, 0.418, 0.864, 0.385, 0.356], [-2.324, -0.32, 0.424, 0.485, 0.66, -0.082], [-1.955, 0.121, 0.148, 0.369, 0.415, 0.131]] C: [[1.282, -0.743, 0.129, 0.493, 0.257, 0.293], [-1.968, -0.763, 0.156, 0.467, 0.241, 0.31], [-1.95, 0.267, 0.16, 0.231, 0.318, 0.302]] D: [[1.109, -0.73, -0.038, 0.564, 0.587, 0.172], [-2.259, -0.589, 0.46, 0.771, -0.144, -0.09], [-1.478, 0.494, 0.535, 0.374, 0.223, 0.643]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_106_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_106_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.628, -0.574, 0.244, 0.629, 0.377, 0.613]] B: [[-0.255, -0.118, 0.331, 1.064, 0.829, 0.169]] C: [[-0.907, -0.799, 0.595, 1.106, -0.043, 0.376]] D: [[-0.149, -0.775, 0.103, 0.329, 0.393, 1.004]]
Given a RGB image and a depth image, please detect the 3D bounding box of the toilet in the scene. The camera pose information includes: the rotation matrix: [[-0.881415, -0.308012, 0.3581], [-0.47008, 0.646119, -0.601294], [-0.046169, -0.698325, -0.71429]]; the translation vector: [3.147524, 1.689608, 1.273114], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.628, -0.574, 0.244, 0.629, 0.377, 0.613]] B: [[-0.255, -0.118, 0.331, 1.064, 0.829, 0.169]] C: [[-0.907, -0.799, 0.595, 1.106, -0.043, 0.376]] D: [[-0.149, -0.775, 0.103, 0.329, 0.393, 1.004]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_107_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_107_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.984, -0.791, 0.71, -0.025, 0.146, 1.95], [-2.845, 0.826, 0.79, -0.018, 2.045, 2.096], [-3.127, 1.767, 1.058, 0.668, 0.751, 1.034], [-2.598, 2.204, 1.456, 0.337, 0.226, 0.622], [-1.681, 2.399, 0.33, 0.897, -0.155, 1.345], [-3.032, -0.879, 1.701, 0.543, 0.324, 1.619], [-2.871, -1.012, 1.112, 0.372, 0.525, 1.953], [-1.989, -1.505, 1.05, 1.013, 0.57, 2.119], [-2.342, -1.032, 1.573, 0.099, 0.665, 2.113], [-1.812, -1.549, 0.936, 0.03, 0.702, 1.331], [-0.897, -1.334, 1.032, -0.375, 0.838, 1.222], [1.073, -1.243, 1.222, 0.074, 0.103, 1.889], [0.684, -1.361, 0.842, 0.81, 0.134, 2.122], [1.681, -0.985, 0.915, -0.15, 0.046, 2.017], [1.499, -1.143, 1.225, 1.125, 0.255, 2.053], [2.518, -0.611, 1.251, 0.147, 0.376, 1.463], [2.78, -0.555, 1.623, 0.321, 0.5, 1.453], [2.607, 0.422, 0.93, 0.428, 2.768, 1.865], [2.929, 2.246, 1.615, 0.791, 0.45, 0.84], [2.894, 2.607, 0.679, 0.418, 0.185, 1.771], [1.91, 1.95, 0.631, 1.792, 0.498, 2.141], [0.968, 2.657, -0.02, 0.142, 0.513, 1.049], [2.739, 1.468, 0.752, 0.297, 1.124, 0.649], [1.999, -0.528, 0.795, 0.19, 0.625, 0.528]] B: [[-1.697, -1.101, 1.32, 0.519, 0.607, 2.31], [-2.793, 0.346, 1.419, 0.299, 1.423, 2.149], [-2.764, 1.638, 1.178, 0.604, 0.448, 0.518], [-2.94, 2.09, 1.372, -0.13, -0.272, 0.296], [-1.734, 2.804, 0.582, 1.396, 0.541, 0.939], [-2.549, -0.196, 1.12, 0.785, 0.411, 1.926], [-2.871, -1.014, 0.799, 0.56, 0.597, 1.935], [-2.659, -0.762, 1.356, 0.825, 0.021, 2.649], [-1.977, -1.011, 1.131, 0.465, 0.035, 2.324], [-1.526, -1.598, 1.392, 0.441, -0.118, 2.102], [-1.353, -0.868, 0.591, 0.125, 0.493, 1.476], [1.173, -1.254, 0.599, -0.335, 0.938, 1.499], [1.444, -1.618, 1.332, 0.376, 0.369, 1.68], [1.582, -1.255, 0.456, -0.034, -0.048, 2.138], [2.452, -1.152, 1.16, 0.41, -0.305, 2.162], [2.246, -1.101, 0.993, 0.065, 0.725, 2.256], [2.414, -0.99, 1.12, 0.836, 0.744, 1.026], [2.607, 0.594, 0.728, -0.103, 2.445, 1.796], [2.075, 1.78, 1.433, 0.826, 1.27, 1.569], [2.842, 2.47, 1.179, 0.437, 0.717, 1.714], [2.073, 1.959, 0.513, 1.293, -0.057, 1.28], [0.684, 2.546, 0.647, 0.281, 0.423, 0.403], [1.985, 2.256, 0.609, 0.323, 0.304, 0.186], [1.904, -0.439, 0.116, 0.205, 0.913, 1.076]] C: [[-0.882, -0.996, 0.828, 0.066, -0.03, 2.259], [-2.906, 0.486, 0.584, 0.338, 1.448, 2.228], [-2.335, 1.79, 1.402, 0.799, 0.604, 0.979], [-2.492, 2.696, 0.852, 0.385, -0.119, 0.551], [-2.113, 2.369, 0.634, 1.634, -0.378, 1.33], [-2.9, -0.382, 1.544, 0.229, 0.561, 1.896], [-2.46, -0.938, 0.92, 0.562, 0.836, 1.812], [-2.236, -1.122, 1.385, 0.806, -0.301, 1.756], [-1.859, -1.439, 0.978, -0.087, 0.007, 2.232], [-1.477, -1.605, 1.119, -0.203, 0.225, 1.352], [-0.558, -1.702, 0.427, 0.133, 0.668, 1.46], [0.818, -0.885, 1.161, 0.455, 0.101, 1.667], [0.552, -1.308, 0.707, 0.978, 0.615, 1.676], [2.109, -1.305, 1.008, -0.007, 0.224, 2.013], [2.016, -1.577, 1.004, 0.572, 0.061, 2.141], [1.754, -1.027, 1.286, 0.147, 0.165, 1.509], [2.849, -0.613, 0.987, 0.617, 1.099, 1.162], [2.281, 0.428, 1.287, 0.612, 2.792, 1.8], [2.1, 1.909, 1.627, 0.042, 0.641, 1.338], [2.025, 1.994, 0.97, 0.816, 0.372, 1.93], [1.678, 2.705, 1.241, 1.93, -0.063, 1.837], [0.582, 2.314, 0.279, 0.554, 0.013, 1.151], [2.245, 1.504, 0.631, 0.05, 1.008, 1.066], [2.09, -0.514, 0.622, -0.006, 1.061, 1.06]] D: [[-1.212, -1.13, 1.017, 0.465, 0.161, 2.011], [-2.56, 0.64, 0.971, 0.201, 1.804, 1.935], [-2.744, 1.914, 1.197, 0.349, 0.771, 0.66], [-2.606, 2.363, 1.087, 0.038, 0.219, 0.424], [-1.931, 2.472, 0.667, 1.366, 0.094, 1.255], [-2.729, -0.603, 1.38, 0.39, 0.792, 1.541], [-2.531, -0.93, 1.084, 0.175, 0.507, 2.172], [-2.227, -1.13, 1.087, 0.723, 0.142, 2.167], [-1.887, -1.279, 1.074, 0.181, 0.413, 2.133], [-1.395, -1.301, 1.124, 0.117, 0.289, 1.814], [-0.99, -1.313, 0.763, 0.122, 0.477, 1.511], [0.768, -1.372, 0.865, 0.144, 0.573, 1.696], [0.958, -1.124, 0.866, 0.51, 0.163, 1.704], [1.687, -1.284, 0.89, 0.172, 0.422, 1.772], [1.97, -1.137, 0.897, 0.705, 0.139, 1.81], [2.237, -1.017, 0.895, 0.302, 0.335, 1.807], [2.506, -0.615, 1.189, 0.456, 0.783, 1.228], [2.295, 0.463, 0.865, 0.248, 2.384, 1.746], [2.549, 1.9, 1.178, 0.43, 0.874, 1.13], [2.396, 2.329, 0.87, 0.323, 0.269, 1.739], [1.621, 2.45, 0.875, 1.651, 0.189, 1.735], [0.789, 2.563, 0.425, 0.113, 0.177, 0.782], [2.336, 1.911, 0.338, 0.211, 0.688, 0.678], [2.287, -0.576, 0.338, 0.14, 0.728, 0.71]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.731293, 0.384445, -0.563394], [0.682011, 0.401944, -0.610984], [-0.008437, -0.831049, -0.556135]]; the translation vector: [5.176627, 2.209938, 1.427488], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.984, -0.791, 0.71, -0.025, 0.146, 1.95], [-2.845, 0.826, 0.79, -0.018, 2.045, 2.096], [-3.127, 1.767, 1.058, 0.668, 0.751, 1.034], [-2.598, 2.204, 1.456, 0.337, 0.226, 0.622], [-1.681, 2.399, 0.33, 0.897, -0.155, 1.345], [-3.032, -0.879, 1.701, 0.543, 0.324, 1.619], [-2.871, -1.012, 1.112, 0.372, 0.525, 1.953], [-1.989, -1.505, 1.05, 1.013, 0.57, 2.119], [-2.342, -1.032, 1.573, 0.099, 0.665, 2.113], [-1.812, -1.549, 0.936, 0.03, 0.702, 1.331], [-0.897, -1.334, 1.032, -0.375, 0.838, 1.222], [1.073, -1.243, 1.222, 0.074, 0.103, 1.889], [0.684, -1.361, 0.842, 0.81, 0.134, 2.122], [1.681, -0.985, 0.915, -0.15, 0.046, 2.017], [1.499, -1.143, 1.225, 1.125, 0.255, 2.053], [2.518, -0.611, 1.251, 0.147, 0.376, 1.463], [2.78, -0.555, 1.623, 0.321, 0.5, 1.453], [2.607, 0.422, 0.93, 0.428, 2.768, 1.865], [2.929, 2.246, 1.615, 0.791, 0.45, 0.84], [2.894, 2.607, 0.679, 0.418, 0.185, 1.771], [1.91, 1.95, 0.631, 1.792, 0.498, 2.141], [0.968, 2.657, -0.02, 0.142, 0.513, 1.049], [2.739, 1.468, 0.752, 0.297, 1.124, 0.649], [1.999, -0.528, 0.795, 0.19, 0.625, 0.528]] B: [[-1.697, -1.101, 1.32, 0.519, 0.607, 2.31], [-2.793, 0.346, 1.419, 0.299, 1.423, 2.149], [-2.764, 1.638, 1.178, 0.604, 0.448, 0.518], [-2.94, 2.09, 1.372, -0.13, -0.272, 0.296], [-1.734, 2.804, 0.582, 1.396, 0.541, 0.939], [-2.549, -0.196, 1.12, 0.785, 0.411, 1.926], [-2.871, -1.014, 0.799, 0.56, 0.597, 1.935], [-2.659, -0.762, 1.356, 0.825, 0.021, 2.649], [-1.977, -1.011, 1.131, 0.465, 0.035, 2.324], [-1.526, -1.598, 1.392, 0.441, -0.118, 2.102], [-1.353, -0.868, 0.591, 0.125, 0.493, 1.476], [1.173, -1.254, 0.599, -0.335, 0.938, 1.499], [1.444, -1.618, 1.332, 0.376, 0.369, 1.68], [1.582, -1.255, 0.456, -0.034, -0.048, 2.138], [2.452, -1.152, 1.16, 0.41, -0.305, 2.162], [2.246, -1.101, 0.993, 0.065, 0.725, 2.256], [2.414, -0.99, 1.12, 0.836, 0.744, 1.026], [2.607, 0.594, 0.728, -0.103, 2.445, 1.796], [2.075, 1.78, 1.433, 0.826, 1.27, 1.569], [2.842, 2.47, 1.179, 0.437, 0.717, 1.714], [2.073, 1.959, 0.513, 1.293, -0.057, 1.28], [0.684, 2.546, 0.647, 0.281, 0.423, 0.403], [1.985, 2.256, 0.609, 0.323, 0.304, 0.186], [1.904, -0.439, 0.116, 0.205, 0.913, 1.076]] C: [[-0.882, -0.996, 0.828, 0.066, -0.03, 2.259], [-2.906, 0.486, 0.584, 0.338, 1.448, 2.228], [-2.335, 1.79, 1.402, 0.799, 0.604, 0.979], [-2.492, 2.696, 0.852, 0.385, -0.119, 0.551], [-2.113, 2.369, 0.634, 1.634, -0.378, 1.33], [-2.9, -0.382, 1.544, 0.229, 0.561, 1.896], [-2.46, -0.938, 0.92, 0.562, 0.836, 1.812], [-2.236, -1.122, 1.385, 0.806, -0.301, 1.756], [-1.859, -1.439, 0.978, -0.087, 0.007, 2.232], [-1.477, -1.605, 1.119, -0.203, 0.225, 1.352], [-0.558, -1.702, 0.427, 0.133, 0.668, 1.46], [0.818, -0.885, 1.161, 0.455, 0.101, 1.667], [0.552, -1.308, 0.707, 0.978, 0.615, 1.676], [2.109, -1.305, 1.008, -0.007, 0.224, 2.013], [2.016, -1.577, 1.004, 0.572, 0.061, 2.141], [1.754, -1.027, 1.286, 0.147, 0.165, 1.509], [2.849, -0.613, 0.987, 0.617, 1.099, 1.162], [2.281, 0.428, 1.287, 0.612, 2.792, 1.8], [2.1, 1.909, 1.627, 0.042, 0.641, 1.338], [2.025, 1.994, 0.97, 0.816, 0.372, 1.93], [1.678, 2.705, 1.241, 1.93, -0.063, 1.837], [0.582, 2.314, 0.279, 0.554, 0.013, 1.151], [2.245, 1.504, 0.631, 0.05, 1.008, 1.066], [2.09, -0.514, 0.622, -0.006, 1.061, 1.06]] D: [[-1.212, -1.13, 1.017, 0.465, 0.161, 2.011], [-2.56, 0.64, 0.971, 0.201, 1.804, 1.935], [-2.744, 1.914, 1.197, 0.349, 0.771, 0.66], [-2.606, 2.363, 1.087, 0.038, 0.219, 0.424], [-1.931, 2.472, 0.667, 1.366, 0.094, 1.255], [-2.729, -0.603, 1.38, 0.39, 0.792, 1.541], [-2.531, -0.93, 1.084, 0.175, 0.507, 2.172], [-2.227, -1.13, 1.087, 0.723, 0.142, 2.167], [-1.887, -1.279, 1.074, 0.181, 0.413, 2.133], [-1.395, -1.301, 1.124, 0.117, 0.289, 1.814], [-0.99, -1.313, 0.763, 0.122, 0.477, 1.511], [0.768, -1.372, 0.865, 0.144, 0.573, 1.696], [0.958, -1.124, 0.866, 0.51, 0.163, 1.704], [1.687, -1.284, 0.89, 0.172, 0.422, 1.772], [1.97, -1.137, 0.897, 0.705, 0.139, 1.81], [2.237, -1.017, 0.895, 0.302, 0.335, 1.807], [2.506, -0.615, 1.189, 0.456, 0.783, 1.228], [2.295, 0.463, 0.865, 0.248, 2.384, 1.746], [2.549, 1.9, 1.178, 0.43, 0.874, 1.13], [2.396, 2.329, 0.87, 0.323, 0.269, 1.739], [1.621, 2.45, 0.875, 1.651, 0.189, 1.735], [0.789, 2.563, 0.425, 0.113, 0.177, 0.782], [2.336, 1.911, 0.338, 0.211, 0.688, 0.678], [2.287, -0.576, 0.338, 0.14, 0.728, 0.71]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_108_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_108_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.196, -0.211, 0.68, 0.711, 0.576, 2.155]] B: [[-0.409, 0.533, 1.267, -0.113, 0.263, 1.631]] C: [[-0.799, 0.234, 0.962, 0.275, 0.234, 1.923]] D: [[-1.167, 0.457, 0.799, -0.179, 0.573, 2.357]]
Given a RGB image and a depth image, please detect the 3D bounding box of the shower curtain in the scene. The camera pose information includes: the rotation matrix: [[-0.506976, -0.449046, 0.735753], [-0.861802, 0.247713, -0.442646], [0.016513, -0.858485, -0.512574]]; the translation vector: [1.568574, 4.423309, 1.333385], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.196, -0.211, 0.68, 0.711, 0.576, 2.155]] B: [[-0.409, 0.533, 1.267, -0.113, 0.263, 1.631]] C: [[-0.799, 0.234, 0.962, 0.275, 0.234, 1.923]] D: [[-1.167, 0.457, 0.799, -0.179, 0.573, 2.357]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_109_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_109_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.94, 1.68, 0.837, 0.663, 0.508, 0.307]] B: [[-1.567, 0.924, 0.596, -0.078, 0.24, 0.881]] C: [[-1.847, 1.274, 0.842, 0.196, 0.441, 0.778]] D: [[-2.041, 1.755, 1.288, 0.168, 0.884, 0.741]]
Given a RGB image and a depth image, please detect the 3D bounding box of the object in the scene. The camera pose information includes: the rotation matrix: [[0.233902, -0.58763, 0.774584], [-0.967246, -0.059828, 0.246692], [-0.098622, -0.806915, -0.582377]]; the translation vector: [0.860343, 3.117731, 1.418568], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.94, 1.68, 0.837, 0.663, 0.508, 0.307]] B: [[-1.567, 0.924, 0.596, -0.078, 0.24, 0.881]] C: [[-1.847, 1.274, 0.842, 0.196, 0.441, 0.778]] D: [[-2.041, 1.755, 1.288, 0.168, 0.884, 0.741]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_110_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_110_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.505, -0.116, 0.747, 0.409, 0.695, 0.297], [-1.441, 0.909, 0.606, 0.695, 0.528, 0.24], [1.536, 0.64, 0.715, 0.483, 0.851, 0.175], [1.546, -0.374, 0.796, 0.374, 0.77, 0.35], [-1.45, 0.754, 0.484, 0.85, 0.766, 0.215]] B: [[1.607, 0.304, 0.83, 0.898, 0.58, 0.697], [-1.406, 0.619, 0.763, 0.933, 0.149, 0.108], [1.448, 0.861, 0.699, 0.254, 0.441, 0.026], [1.945, -0.851, 0.97, 0.08, 1.051, 0.781], [-1.319, 0.842, 0.31, 1.314, 0.811, 0.161]] C: [[1.451, -0.224, 1.202, 0.474, 0.259, 0.177], [-1.303, 1.145, 0.291, 1.141, 0.346, 0.272], [1.763, 0.401, 0.944, 0.92, 1.062, -0.044], [1.663, -0.056, 0.805, 0.848, 1.189, 0.211], [-1.93, 0.603, 0.76, 0.741, 0.586, -0.206]] D: [[1.888, 0.164, 1.08, 0.295, 0.332, 0.729], [-1.781, 1.348, 0.164, 0.674, 0.738, 0.722], [1.997, 0.742, 0.991, 0.029, 0.449, -0.1], [1.487, 0.076, 0.6, 0.156, 0.445, 0.145], [-1.75, 1.16, 0.275, 0.799, 1.235, 0.304]]
Given a RGB image and a depth image, please detect the 3D bounding box of the pillow in the scene. The camera pose information includes: the rotation matrix: [[0.484778, 0.389748, -0.782998], [0.874059, -0.248441, 0.417491], [-0.031813, -0.886777, -0.461102]]; the translation vector: [2.948564, 2.712566, 1.480667], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.505, -0.116, 0.747, 0.409, 0.695, 0.297], [-1.441, 0.909, 0.606, 0.695, 0.528, 0.24], [1.536, 0.64, 0.715, 0.483, 0.851, 0.175], [1.546, -0.374, 0.796, 0.374, 0.77, 0.35], [-1.45, 0.754, 0.484, 0.85, 0.766, 0.215]] B: [[1.607, 0.304, 0.83, 0.898, 0.58, 0.697], [-1.406, 0.619, 0.763, 0.933, 0.149, 0.108], [1.448, 0.861, 0.699, 0.254, 0.441, 0.026], [1.945, -0.851, 0.97, 0.08, 1.051, 0.781], [-1.319, 0.842, 0.31, 1.314, 0.811, 0.161]] C: [[1.451, -0.224, 1.202, 0.474, 0.259, 0.177], [-1.303, 1.145, 0.291, 1.141, 0.346, 0.272], [1.763, 0.401, 0.944, 0.92, 1.062, -0.044], [1.663, -0.056, 0.805, 0.848, 1.189, 0.211], [-1.93, 0.603, 0.76, 0.741, 0.586, -0.206]] D: [[1.888, 0.164, 1.08, 0.295, 0.332, 0.729], [-1.781, 1.348, 0.164, 0.674, 0.738, 0.722], [1.997, 0.742, 0.991, 0.029, 0.449, -0.1], [1.487, 0.076, 0.6, 0.156, 0.445, 0.145], [-1.75, 1.16, 0.275, 0.799, 1.235, 0.304]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_111_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_111_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.148, -1.819, 0.681, 1.73, 0.9, 0.465], [-1.44, 2.208, 0.821, 0.893, 2.303, 0.634], [0.765, 1.362, 0.255, 2.131, 1.052, 0.327], [-1.998, -1.691, 0.062, 1.757, 1.835, 0.718]] B: [[1.542, -1.233, 0.854, 2.268, 1.021, 0.755], [-2.098, 1.815, 0.076, 0.977, 1.531, 0.579], [1.499, 1.894, 0.799, 1.364, 1.243, 0.606], [-1.591, -1.777, -0.089, 1.375, 2.302, 0.818]] C: [[1.019, -1.513, 0.012, 1.939, 1.04, 0.603], [-1.397, 1.894, 0.192, 1.788, 2.263, 0.963], [0.794, 1.72, 0.728, 1.503, 1.344, 0.994], [-1.899, -1.035, 0.107, 1.802, 1.941, 0.705]] D: [[1.181, -1.566, 0.434, 1.91, 1.342, 0.847], [-1.636, 1.86, 0.387, 1.322, 1.894, 0.782], [1.234, 1.651, 0.4, 1.847, 1.393, 0.784], [-1.767, -1.535, 0.407, 1.331, 1.981, 0.802]]
Given a RGB image and a depth image, please detect the 3D bounding box of the table in the scene. The camera pose information includes: the rotation matrix: [[0.996822, -0.027813, -0.074656], [0.056495, -0.413943, 0.908548], [-0.056173, -0.909878, -0.411056]]; the translation vector: [4.405487, 5.403347, 1.494535], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.148, -1.819, 0.681, 1.73, 0.9, 0.465], [-1.44, 2.208, 0.821, 0.893, 2.303, 0.634], [0.765, 1.362, 0.255, 2.131, 1.052, 0.327], [-1.998, -1.691, 0.062, 1.757, 1.835, 0.718]] B: [[1.542, -1.233, 0.854, 2.268, 1.021, 0.755], [-2.098, 1.815, 0.076, 0.977, 1.531, 0.579], [1.499, 1.894, 0.799, 1.364, 1.243, 0.606], [-1.591, -1.777, -0.089, 1.375, 2.302, 0.818]] C: [[1.019, -1.513, 0.012, 1.939, 1.04, 0.603], [-1.397, 1.894, 0.192, 1.788, 2.263, 0.963], [0.794, 1.72, 0.728, 1.503, 1.344, 0.994], [-1.899, -1.035, 0.107, 1.802, 1.941, 0.705]] D: [[1.181, -1.566, 0.434, 1.91, 1.342, 0.847], [-1.636, 1.86, 0.387, 1.322, 1.894, 0.782], [1.234, 1.651, 0.4, 1.847, 1.393, 0.784], [-1.767, -1.535, 0.407, 1.331, 1.981, 0.802]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_112_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_112_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.632, 2.861, 0.973, 0.851, 0.88, 0.553]] B: [[2.217, 3.039, 0.859, 0.578, 0.679, 0.811]] C: [[2.372, 2.508, 1.395, 0.466, 0.758, 0.941]] D: [[2.418, 3.313, 1.363, 0.462, 1.217, 0.869]]
Given a RGB image and a depth image, please detect the 3D bounding box of the tv in the scene. The camera pose information includes: the rotation matrix: [[-0.869565, 0.231948, -0.435955], [0.492522, 0.471291, -0.731647], [0.035758, -0.850932, -0.524058]]; the translation vector: [2.750575, 3.154689, 1.290553], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[2.632, 2.861, 0.973, 0.851, 0.88, 0.553]] B: [[2.217, 3.039, 0.859, 0.578, 0.679, 0.811]] C: [[2.372, 2.508, 1.395, 0.466, 0.758, 0.941]] D: [[2.418, 3.313, 1.363, 0.462, 1.217, 0.869]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_113_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_113_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.523, -0.73, 1.669, 0.473, 3.389, 1.19]] B: [[-2.737, -0.956, 1.441, 0.102, 2.891, 0.9]] C: [[-2.415, -1.042, 1.71, -0.167, 2.518, 1.307]] D: [[-3.121, -1.319, 1.73, 0.166, 2.406, 0.532]]
Given a RGB image and a depth image, please detect the 3D bounding box of the board in the scene. The camera pose information includes: the rotation matrix: [[0.896132, -0.052356, 0.440688], [-0.436974, -0.277444, 0.855616], [0.07747, -0.959314, -0.271505]]; the translation vector: [3.211431, 3.110947, 1.584554], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-2.523, -0.73, 1.669, 0.473, 3.389, 1.19]] B: [[-2.737, -0.956, 1.441, 0.102, 2.891, 0.9]] C: [[-2.415, -1.042, 1.71, -0.167, 2.518, 1.307]] D: [[-3.121, -1.319, 1.73, 0.166, 2.406, 0.532]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_114_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_114_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.919, 2.881, 0.5, 1.076, 0.198, 0.512], [-0.387, 3.021, 0.763, 1.206, 0.18, 1.044]] B: [[0.967, 3.235, 0.454, 1.103, -0.268, 0.912], [-0.093, 2.837, 0.491, 1.606, 0.643, 1.265]] C: [[1.146, 2.813, 0.895, 1.333, -0.231, 0.884], [-0.108, 2.697, 0.646, 1.144, -0.245, 0.801]] D: [[1.405, 2.769, 0.583, 0.816, -0.053, 0.839], [-0.646, 2.953, 0.434, 1.464, 0.436, 0.68]]
Given a RGB image and a depth image, please detect the 3D bounding box of the mirror in the scene. The camera pose information includes: the rotation matrix: [[-0.880278, -0.246293, 0.405524], [-0.473973, 0.417832, -0.775091], [0.021459, -0.874503, -0.484545]]; the translation vector: [3.281806, 2.754624, 1.352781], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.919, 2.881, 0.5, 1.076, 0.198, 0.512], [-0.387, 3.021, 0.763, 1.206, 0.18, 1.044]] B: [[0.967, 3.235, 0.454, 1.103, -0.268, 0.912], [-0.093, 2.837, 0.491, 1.606, 0.643, 1.265]] C: [[1.146, 2.813, 0.895, 1.333, -0.231, 0.884], [-0.108, 2.697, 0.646, 1.144, -0.245, 0.801]] D: [[1.405, 2.769, 0.583, 0.816, -0.053, 0.839], [-0.646, 2.953, 0.434, 1.464, 0.436, 0.68]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_115_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_115_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.099, -1.623, 0.8, 1.091, 0.185, 1.674]] B: [[0.028, -1.324, 1.283, 0.847, -0.251, 1.976]] C: [[0.008, -1.165, 1.014, 1.132, -0.028, 1.19]] D: [[0.219, -1.325, 0.313, 1.01, 0.321, 1.757]]
Given a RGB image and a depth image, please detect the 3D bounding box of the doorframe in the scene. The camera pose information includes: the rotation matrix: [[-0.874867, -0.0675, 0.479638], [-0.482919, 0.197999, -0.852987], [-0.037391, -0.977875, -0.205819]]; the translation vector: [2.397274, 1.722858, 1.486845], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.099, -1.623, 0.8, 1.091, 0.185, 1.674]] B: [[0.028, -1.324, 1.283, 0.847, -0.251, 1.976]] C: [[0.008, -1.165, 1.014, 1.132, -0.028, 1.19]] D: [[0.219, -1.325, 0.313, 1.01, 0.321, 1.757]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_116_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_116_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.712, -1.245, 0.91, 1.048, 1.199, 2.013]] B: [[0.626, -1.611, 1.221, 1.09, 1.245, 2.069]] C: [[1.138, -1.446, 0.77, 0.846, 1.373, 1.96]] D: [[0.371, -1.441, 0.499, 0.655, 1.441, 2.321]]
Given a RGB image and a depth image, please detect the 3D bounding box of the shower in the scene. The camera pose information includes: the rotation matrix: [[-0.612656, -0.411508, 0.674769], [-0.789543, 0.280105, -0.546043], [0.035694, -0.867296, -0.496511]]; the translation vector: [1.897828, 2.372103, 1.388776], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.712, -1.245, 0.91, 1.048, 1.199, 2.013]] B: [[0.626, -1.611, 1.221, 1.09, 1.245, 2.069]] C: [[1.138, -1.446, 0.77, 0.846, 1.373, 1.96]] D: [[0.371, -1.441, 0.499, 0.655, 1.441, 2.321]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_117_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_117_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.851, -0.281, 1.012, 0.232, 0.838, 2.123]] B: [[-0.647, 0.167, 1.047, -0.111, 0.572, 1.688]] C: [[-0.968, -0.496, 1.046, -0.014, 1.192, 1.751]] D: [[-0.616, -0.07, 1.075, 0.231, 1.203, 1.991]]
Given a RGB image and a depth image, please detect the 3D bounding box of the doorframe in the scene. The camera pose information includes: the rotation matrix: [[-0.48142, 0.335029, -0.809933], [0.872625, 0.096524, -0.478757], [-0.08222, -0.937251, -0.338823]]; the translation vector: [4.429162, 2.287411, 1.464776], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.851, -0.281, 1.012, 0.232, 0.838, 2.123]] B: [[-0.647, 0.167, 1.047, -0.111, 0.572, 1.688]] C: [[-0.968, -0.496, 1.046, -0.014, 1.192, 1.751]] D: [[-0.616, -0.07, 1.075, 0.231, 1.203, 1.991]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_118_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_118_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.76, 1.613, 0.501, 0.748, 1.477, 2.283], [-1.256, 0.486, 0.695, 0.261, -0.004, 1.392]] B: [[1.66, 0.843, 1.041, 1.024, 1.548, 1.575], [-0.68, 1.177, 0.879, 0.467, 0.635, 2.319]] C: [[1.906, 1.059, 1.056, 0.263, 1.047, 1.4], [-0.793, 1.238, 0.654, 0.903, 0.438, 1.901]] D: [[1.788, 1.153, 0.954, 0.56, 1.154, 1.881], [-0.939, 0.896, 0.911, 0.636, 0.225, 1.837]]
Given a RGB image and a depth image, please detect the 3D bounding box of the door in the scene. The camera pose information includes: the rotation matrix: [[-0.414473, -0.491559, 0.765887], [-0.909569, 0.196057, -0.366396], [0.029948, -0.848488, -0.528367]]; the translation vector: [0.955419, 3.497842, 1.497559], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.76, 1.613, 0.501, 0.748, 1.477, 2.283], [-1.256, 0.486, 0.695, 0.261, -0.004, 1.392]] B: [[1.66, 0.843, 1.041, 1.024, 1.548, 1.575], [-0.68, 1.177, 0.879, 0.467, 0.635, 2.319]] C: [[1.906, 1.059, 1.056, 0.263, 1.047, 1.4], [-0.793, 1.238, 0.654, 0.903, 0.438, 1.901]] D: [[1.788, 1.153, 0.954, 0.56, 1.154, 1.881], [-0.939, 0.896, 0.911, 0.636, 0.225, 1.837]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_119_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_119_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.054, 1.184, 0.861, 1.846, 0.937, 1.341]] B: [[0.486, 0.802, 0.412, 1.751, 1.322, 0.856]] C: [[0.138, 0.31, 0.136, 1.361, 1.636, 1.27]] D: [[0.461, 1.003, 0.863, 1.591, 0.946, 0.97]]
Given a RGB image and a depth image, please detect the 3D bounding box of the bed in the scene. The camera pose information includes: the rotation matrix: [[-0.778266, 0.076502, -0.623257], [0.626532, 0.028295, -0.778882], [-0.041951, -0.996668, -0.069952]]; the translation vector: [4.354075, 2.27787, 1.510689], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.054, 1.184, 0.861, 1.846, 0.937, 1.341]] B: [[0.486, 0.802, 0.412, 1.751, 1.322, 0.856]] C: [[0.138, 0.31, 0.136, 1.361, 1.636, 1.27]] D: [[0.461, 1.003, 0.863, 1.591, 0.946, 0.97]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_120_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_120_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.119, 2.382, -1.353, 2.688, 3.135, 0.067], [0.13, -2.518, 2.241, 3.948, 1.36, 0.679], [-0.552, 1.97, 3.469, 0.872, 1.36, 0.237]] B: [[1.56, 2.895, -0.877, 2.03, 3.162, 0.481], [-0.012, -2.383, 2.434, 3.863, 1.73, 0.8], [-1.053, 2.303, 3.432, 0.863, 1.12, -0.287]] C: [[1.156, 2.743, -1.086, 2.211, 3.278, 0.076], [-0.143, -2.063, 2.035, 4.283, 1.757, 0.379], [-1.038, 2.35, 3.4, 1.326, 1.515, 0.161]] D: [[1.559, 2.394, -0.855, 1.997, 3.635, -0.357], [-0.381, -2.532, 1.718, 3.949, 1.906, 0.055], [-0.752, 2.698, 2.911, 0.92, 1.137, -0.299]]
Given a RGB image and a depth image, please detect the 3D bounding box of the floor in the scene. The camera pose information includes: the rotation matrix: [[0.485844, -0.617081, 0.619005], [-0.873216, -0.311825, 0.374512], [-0.038083, -0.722479, -0.690343]]; the translation vector: [-0.164865, 3.073333, 1.323993], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.119, 2.382, -1.353, 2.688, 3.135, 0.067], [0.13, -2.518, 2.241, 3.948, 1.36, 0.679], [-0.552, 1.97, 3.469, 0.872, 1.36, 0.237]] B: [[1.56, 2.895, -0.877, 2.03, 3.162, 0.481], [-0.012, -2.383, 2.434, 3.863, 1.73, 0.8], [-1.053, 2.303, 3.432, 0.863, 1.12, -0.287]] C: [[1.156, 2.743, -1.086, 2.211, 3.278, 0.076], [-0.143, -2.063, 2.035, 4.283, 1.757, 0.379], [-1.038, 2.35, 3.4, 1.326, 1.515, 0.161]] D: [[1.559, 2.394, -0.855, 1.997, 3.635, -0.357], [-0.381, -2.532, 1.718, 3.949, 1.906, 0.055], [-0.752, 2.698, 2.911, 0.92, 1.137, -0.299]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_121_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_121_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.806, 0.963, 2.18, -0.15, 0.284, 0.747], [1.781, 1.911, 0.25, 0.639, -0.36, 0.423], [0.587, 2.601, 0.863, 0.066, -0.232, 0.753], [-0.114, 0.242, -0.467, -0.049, 0.569, 0.595], [1.888, 2.229, 0.499, -0.382, 0.046, 0.309], [1.509, 1.846, 0.444, -0.228, 0.075, -0.285]] B: [[2.196, 0.809, 1.96, 0.418, -0.322, 0.279], [1.469, 1.583, 0.002, 0.664, -0.01, 0.038], [-0.066, 2.119, 1.533, 0.754, 0.595, 0.72], [0.503, 0.542, -0.003, 0.788, 0.94, -0.045], [2.066, 1.491, 0.9, -0.225, 0.433, 0.456], [1.952, 1.903, 0.373, -0.138, 0.52, 0.69]] C: [[2.185, 1.438, 1.612, -0.033, 0.189, 0.171], [2.033, 1.77, 0.709, 0.481, 0.536, -0.285], [-0.228, 2.34, 1.714, 0.595, 0.3, -0.06], [-0.139, 0.192, -0.291, 0.431, 0.48, -0.343], [2.39, 1.84, 0.691, -0.012, 0.252, 0.48], [1.891, 1.81, 0.417, -0.052, -0.296, 0.438]] D: [[2.211, 1.285, 1.775, 0.127, 0.174, 0.292], [1.829, 1.683, 0.248, 0.278, 0.134, 0.131], [0.255, 2.241, 1.304, 0.333, 0.221, 0.253], [0.094, 0.321, -0.047, 0.34, 0.473, 0.108], [1.975, 1.944, 0.507, 0.101, 0.048, 0.175], [1.799, 1.959, 0.282, 0.261, 0.114, 0.195]]
Given a RGB image and a depth image, please detect the 3D bounding box of the object in the scene. The camera pose information includes: the rotation matrix: [[-0.877021, 0.121711, -0.464779], [0.46491, 0.459041, -0.75706], [0.12121, -0.880038, -0.459173]]; the translation vector: [3.922419, 3.230202, 1.747047], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.806, 0.963, 2.18, -0.15, 0.284, 0.747], [1.781, 1.911, 0.25, 0.639, -0.36, 0.423], [0.587, 2.601, 0.863, 0.066, -0.232, 0.753], [-0.114, 0.242, -0.467, -0.049, 0.569, 0.595], [1.888, 2.229, 0.499, -0.382, 0.046, 0.309], [1.509, 1.846, 0.444, -0.228, 0.075, -0.285]] B: [[2.196, 0.809, 1.96, 0.418, -0.322, 0.279], [1.469, 1.583, 0.002, 0.664, -0.01, 0.038], [-0.066, 2.119, 1.533, 0.754, 0.595, 0.72], [0.503, 0.542, -0.003, 0.788, 0.94, -0.045], [2.066, 1.491, 0.9, -0.225, 0.433, 0.456], [1.952, 1.903, 0.373, -0.138, 0.52, 0.69]] C: [[2.185, 1.438, 1.612, -0.033, 0.189, 0.171], [2.033, 1.77, 0.709, 0.481, 0.536, -0.285], [-0.228, 2.34, 1.714, 0.595, 0.3, -0.06], [-0.139, 0.192, -0.291, 0.431, 0.48, -0.343], [2.39, 1.84, 0.691, -0.012, 0.252, 0.48], [1.891, 1.81, 0.417, -0.052, -0.296, 0.438]] D: [[2.211, 1.285, 1.775, 0.127, 0.174, 0.292], [1.829, 1.683, 0.248, 0.278, 0.134, 0.131], [0.255, 2.241, 1.304, 0.333, 0.221, 0.253], [0.094, 0.321, -0.047, 0.34, 0.473, 0.108], [1.975, 1.944, 0.507, 0.101, 0.048, 0.175], [1.799, 1.959, 0.282, 0.261, 0.114, 0.195]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_122_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_122_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.687, 1.332, 0.035, 0.175, 2.444, 0.931], [-0.771, -0.087, 1.874, 0.351, 2.708, 1.076], [1.073, -0.054, 0.17, 0.668, 1.99, 0.53], [0.962, 0.659, 2.221, 0.281, 1.867, 1.287]] B: [[-0.793, 1.344, 0.264, -0.144, 2.319, 0.303], [-0.892, -0.228, 1.276, 0.428, 2.505, 1.37], [0.859, 0.126, 0.332, 0.439, 1.529, 0.603], [0.425, 0.012, 2.016, 0.908, 2.008, 0.841]] C: [[-1.133, 0.424, 0.86, -0.054, 2.382, 0.943], [-1.282, -0.466, 1.739, 0.288, 2.29, 1.182], [0.76, 0.578, 0.124, 0.797, 1.631, 0.597], [0.974, 0.003, 1.857, 0.274, 1.983, 0.737]] D: [[-0.66, 0.92, 0.369, 0.068, 2.758, 0.803], [-0.938, -0.063, 1.743, 0.134, 2.421, 0.981], [0.672, 0.378, 0.36, 0.646, 1.681, 0.828], [0.776, 0.348, 1.743, 0.449, 1.71, 0.968]]
Given a RGB image and a depth image, please detect the 3D bounding box of the kitchen cabinets in the scene. The camera pose information includes: the rotation matrix: [[0.815869, 0.244354, -0.524069], [0.578211, -0.336271, 0.743367], [0.005416, -0.909513, -0.415641]]; the translation vector: [2.358014, 1.230078, 1.369842], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.687, 1.332, 0.035, 0.175, 2.444, 0.931], [-0.771, -0.087, 1.874, 0.351, 2.708, 1.076], [1.073, -0.054, 0.17, 0.668, 1.99, 0.53], [0.962, 0.659, 2.221, 0.281, 1.867, 1.287]] B: [[-0.793, 1.344, 0.264, -0.144, 2.319, 0.303], [-0.892, -0.228, 1.276, 0.428, 2.505, 1.37], [0.859, 0.126, 0.332, 0.439, 1.529, 0.603], [0.425, 0.012, 2.016, 0.908, 2.008, 0.841]] C: [[-1.133, 0.424, 0.86, -0.054, 2.382, 0.943], [-1.282, -0.466, 1.739, 0.288, 2.29, 1.182], [0.76, 0.578, 0.124, 0.797, 1.631, 0.597], [0.974, 0.003, 1.857, 0.274, 1.983, 0.737]] D: [[-0.66, 0.92, 0.369, 0.068, 2.758, 0.803], [-0.938, -0.063, 1.743, 0.134, 2.421, 0.981], [0.672, 0.378, 0.36, 0.646, 1.681, 0.828], [0.776, 0.348, 1.743, 0.449, 1.71, 0.968]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_123_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_123_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.177, -0.077, 0.773, 0.974, 8.45, 1.181]] B: [[1.408, -0.085, 0.96, 1.256, 8.826, 1.391]] C: [[1.29, 0.138, 0.989, 1.682, 8.854, 1.495]] D: [[1.087, -0.264, 0.505, 1.705, 9.131, 0.904]]
Given a RGB image and a depth image, please detect the 3D bounding box of the blinds in the scene. The camera pose information includes: the rotation matrix: [[0.117057, -0.769276, 0.628102], [-0.987232, -0.021336, 0.157855], [-0.108033, -0.638561, -0.761951]]; the translation vector: [1.032686, 1.226834, 2.186959], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.177, -0.077, 0.773, 0.974, 8.45, 1.181]] B: [[1.408, -0.085, 0.96, 1.256, 8.826, 1.391]] C: [[1.29, 0.138, 0.989, 1.682, 8.854, 1.495]] D: [[1.087, -0.264, 0.505, 1.705, 9.131, 0.904]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_124_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_124_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.333, 1.449, 0.466, 0.575, 0.885, 0.579], [-0.819, 0.179, 1.256, -0.187, 0.08, 0.261], [-0.881, -0.764, 1.817, 0.04, 0.55, 0.119], [-0.782, -0.821, 1.039, -0.465, -0.079, -0.041]] B: [[0.913, 1.406, 0.914, 0.154, 0.729, 0.951], [-0.918, 0.236, 1.614, 0.027, 0.343, 0.415], [-0.932, -0.471, 1.376, 0.043, 0.42, 0.318], [-0.937, -1.266, 1.202, 0.021, 0.397, 0.404]] C: [[0.638, 1.511, 1.273, 0.574, 0.958, 0.746], [-1.165, 0.389, 1.897, 0.474, -0.02, 0.527], [-0.474, 0.021, 1.802, 0.289, 0.006, -0.062], [-1.35, -1.672, 1.153, 0.07, 0.246, 0.557]] D: [[0.615, 1.775, 1.082, 0.394, 0.94, 1.366], [-0.883, -0.231, 1.634, -0.385, 0.134, 0.914], [-0.757, -0.827, 1.097, 0.253, 0.741, 0.546], [-1.013, -1.459, 1.475, -0.37, 0.862, 0.783]]
Given a RGB image and a depth image, please detect the 3D bounding box of the picture in the scene. The camera pose information includes: the rotation matrix: [[-0.042655, 0.409797, -0.911179], [0.998036, -0.024411, -0.0577], [-0.045888, -0.91185, -0.40795]]; the translation vector: [2.423933, 1.356295, 3.282493], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.333, 1.449, 0.466, 0.575, 0.885, 0.579], [-0.819, 0.179, 1.256, -0.187, 0.08, 0.261], [-0.881, -0.764, 1.817, 0.04, 0.55, 0.119], [-0.782, -0.821, 1.039, -0.465, -0.079, -0.041]] B: [[0.913, 1.406, 0.914, 0.154, 0.729, 0.951], [-0.918, 0.236, 1.614, 0.027, 0.343, 0.415], [-0.932, -0.471, 1.376, 0.043, 0.42, 0.318], [-0.937, -1.266, 1.202, 0.021, 0.397, 0.404]] C: [[0.638, 1.511, 1.273, 0.574, 0.958, 0.746], [-1.165, 0.389, 1.897, 0.474, -0.02, 0.527], [-0.474, 0.021, 1.802, 0.289, 0.006, -0.062], [-1.35, -1.672, 1.153, 0.07, 0.246, 0.557]] D: [[0.615, 1.775, 1.082, 0.394, 0.94, 1.366], [-0.883, -0.231, 1.634, -0.385, 0.134, 0.914], [-0.757, -0.827, 1.097, 0.253, 0.741, 0.546], [-1.013, -1.459, 1.475, -0.37, 0.862, 0.783]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_125_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_125_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.696, 2.84, 0.243, 0.913, 0.14, 0.965], [-2.524, -1.89, 1.517, 0.263, 1.169, 1.097]] B: [[-2.032, 3.081, 0.673, 0.874, 0.207, 1.282], [-2.435, -2.167, 1.207, 0.214, 0.953, 0.8]] C: [[-2.083, 2.817, 0.915, 0.407, -0.083, 1.119], [-2.185, -1.778, 0.77, 0.561, 0.888, 0.902]] D: [[-1.79, 3.485, 0.577, 0.547, 0.315, 1.286], [-2.516, -2.509, 1.071, 0.577, 1.197, 0.616]]
Given a RGB image and a depth image, please detect the 3D bounding box of the window in the scene. The camera pose information includes: the rotation matrix: [[0.299058, 0.37418, -0.877812], [0.95368, -0.085842, 0.288314], [0.032528, -0.923375, -0.38252]]; the translation vector: [3.908031, 4.993837, 1.41318], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.696, 2.84, 0.243, 0.913, 0.14, 0.965], [-2.524, -1.89, 1.517, 0.263, 1.169, 1.097]] B: [[-2.032, 3.081, 0.673, 0.874, 0.207, 1.282], [-2.435, -2.167, 1.207, 0.214, 0.953, 0.8]] C: [[-2.083, 2.817, 0.915, 0.407, -0.083, 1.119], [-2.185, -1.778, 0.77, 0.561, 0.888, 0.902]] D: [[-1.79, 3.485, 0.577, 0.547, 0.315, 1.286], [-2.516, -2.509, 1.071, 0.577, 1.197, 0.616]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_126_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_126_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.147, 0.119, 0.251, 0.463, 0.502, 0.493], [1.142, -0.546, 0.997, 0.457, 0.597, 0.473], [1.198, 0.632, 0.925, 0.452, 0.473, 0.432], [1.163, 0.092, 1.069, 0.44, 0.432, 0.506]] B: [[0.939, -0.362, 0.676, 0.67, 0.041, 0.58], [0.766, -0.402, 0.786, 0.189, 1.052, 0.915], [1.684, 0.428, 1.283, 0.635, 0.353, 0.864], [1.275, -0.104, 1.385, 0.008, 0.054, 0.956]] C: [[1.248, 0.165, 0.549, 0.255, 0.722, 0.454], [1.139, -0.967, 1.065, 0.247, 0.425, 0.531], [0.839, 1.106, 1.224, 0.271, 0.846, 0.671], [0.954, 0.329, 1.422, 0.774, 0.624, 0.313]] D: [[1.328, 0.233, 0.409, 0.859, 0.672, 0.071], [1.492, -0.434, 0.743, 0.731, 0.907, 0.382], [1.626, 0.478, 0.601, 0.312, 0.631, 0.904], [1.629, 0.385, 0.684, 0.845, 0.492, 0.801]]
Given a RGB image and a depth image, please detect the 3D bounding box of the printer in the scene. The camera pose information includes: the rotation matrix: [[0.985254, -0.134646, 0.105573], [-0.142287, -0.302097, 0.942599], [-0.095024, -0.94372, -0.3168]]; the translation vector: [1.134605, 1.549487, 1.505245], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.147, 0.119, 0.251, 0.463, 0.502, 0.493], [1.142, -0.546, 0.997, 0.457, 0.597, 0.473], [1.198, 0.632, 0.925, 0.452, 0.473, 0.432], [1.163, 0.092, 1.069, 0.44, 0.432, 0.506]] B: [[0.939, -0.362, 0.676, 0.67, 0.041, 0.58], [0.766, -0.402, 0.786, 0.189, 1.052, 0.915], [1.684, 0.428, 1.283, 0.635, 0.353, 0.864], [1.275, -0.104, 1.385, 0.008, 0.054, 0.956]] C: [[1.248, 0.165, 0.549, 0.255, 0.722, 0.454], [1.139, -0.967, 1.065, 0.247, 0.425, 0.531], [0.839, 1.106, 1.224, 0.271, 0.846, 0.671], [0.954, 0.329, 1.422, 0.774, 0.624, 0.313]] D: [[1.328, 0.233, 0.409, 0.859, 0.672, 0.071], [1.492, -0.434, 0.743, 0.731, 0.907, 0.382], [1.626, 0.478, 0.601, 0.312, 0.631, 0.904], [1.629, 0.385, 0.684, 0.845, 0.492, 0.801]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_127_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_127_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.978, 2.218, 0.88, 0.413, 0.1, 0.702], [-1.917, 2.1, 1.145, 0.538, 0.288, 0.643]] B: [[-1.584, 2.193, 0.205, 0.199, 0.268, 0.839], [-1.535, 2.333, 0.994, 0.342, 0.187, 0.134]] C: [[-1.966, 2.066, 0.622, 0.287, 0.189, 0.88], [-1.737, 2.041, 0.848, 0.173, 0.149, 0.382]] D: [[-1.998, 2.157, 0.963, 0.629, -0.078, 1.235], [-1.653, 2.214, 0.646, 0.156, 0.285, 0.243]]
Given a RGB image and a depth image, please detect the 3D bounding box of the towel in the scene. The camera pose information includes: the rotation matrix: [[0.686341, -0.358824, 0.632599], [-0.727213, -0.35045, 0.590209], [0.009912, -0.865119, -0.50147]]; the translation vector: [2.486494, 4.601647, 1.455454], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.978, 2.218, 0.88, 0.413, 0.1, 0.702], [-1.917, 2.1, 1.145, 0.538, 0.288, 0.643]] B: [[-1.584, 2.193, 0.205, 0.199, 0.268, 0.839], [-1.535, 2.333, 0.994, 0.342, 0.187, 0.134]] C: [[-1.966, 2.066, 0.622, 0.287, 0.189, 0.88], [-1.737, 2.041, 0.848, 0.173, 0.149, 0.382]] D: [[-1.998, 2.157, 0.963, 0.629, -0.078, 1.235], [-1.653, 2.214, 0.646, 0.156, 0.285, 0.243]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_128_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_128_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.047, -0.588, -0.114, 0.759, 2.976, 0.961]] B: [[-1.511, -0.608, 0.081, 1.102, 2.98, 1.011]] C: [[-1.203, -0.385, 0.359, 0.756, 2.647, 0.817]] D: [[-1.37, -0.358, 0.323, 0.77, 2.437, 0.409]]
Given a RGB image and a depth image, please detect the 3D bounding box of the desk in the scene. The camera pose information includes: the rotation matrix: [[-0.802837, 0.056561, -0.593509], [0.596192, 0.071654, -0.799638], [-0.002701, -0.995825, -0.091248]]; the translation vector: [2.583219, 4.008804, 1.439254], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.047, -0.588, -0.114, 0.759, 2.976, 0.961]] B: [[-1.511, -0.608, 0.081, 1.102, 2.98, 1.011]] C: [[-1.203, -0.385, 0.359, 0.756, 2.647, 0.817]] D: [[-1.37, -0.358, 0.323, 0.77, 2.437, 0.409]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_129_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_129_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.904, -0.732, 0.092, 0.243, 0.59, 0.859], [-1.501, -0.76, 0.757, 1.132, 0.498, 0.756]] B: [[1.126, -0.366, 0.392, 0.688, 0.942, 0.802], [-1.375, -0.274, 0.471, 1.076, 0.886, 0.947]] C: [[0.868, -0.772, 0.151, 0.633, 1.223, 0.791], [-1.775, -0.718, 0.331, 1.093, 0.846, 1.4]] D: [[1.114, -0.309, 0.254, 0.953, 0.846, 0.427], [-1.752, 0.101, 0.877, 0.811, 1.045, 0.651]]
Given a RGB image and a depth image, please detect the 3D bounding box of the dresser in the scene. The camera pose information includes: the rotation matrix: [[-0.442667, -0.46733, 0.765277], [-0.896368, 0.253361, -0.363776], [-0.023888, -0.847001, -0.531054]]; the translation vector: [2.453469, 1.905797, 1.451684], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.904, -0.732, 0.092, 0.243, 0.59, 0.859], [-1.501, -0.76, 0.757, 1.132, 0.498, 0.756]] B: [[1.126, -0.366, 0.392, 0.688, 0.942, 0.802], [-1.375, -0.274, 0.471, 1.076, 0.886, 0.947]] C: [[0.868, -0.772, 0.151, 0.633, 1.223, 0.791], [-1.775, -0.718, 0.331, 1.093, 0.846, 1.4]] D: [[1.114, -0.309, 0.254, 0.953, 0.846, 0.427], [-1.752, 0.101, 0.877, 0.811, 1.045, 0.651]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_130_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_130_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.61, -0.414, 0.408, 4.655, 4.102, -0.244]] B: [[0.311, -0.524, 0.039, 4.829, 4.569, 0.162]] C: [[0.203, -0.323, 0.325, 5.217, 4.229, 0.65]] D: [[0.089, -0.712, 0.114, 5.287, 4.148, 0.629]]
Given a RGB image and a depth image, please detect the 3D bounding box of the floor in the scene. The camera pose information includes: the rotation matrix: [[0.633294, -0.360819, 0.684652], [-0.773758, -0.312806, 0.550863], [0.015401, -0.878613, -0.477285]]; the translation vector: [3.241882, 3.386626, 1.367882], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.61, -0.414, 0.408, 4.655, 4.102, -0.244]] B: [[0.311, -0.524, 0.039, 4.829, 4.569, 0.162]] C: [[0.203, -0.323, 0.325, 5.217, 4.229, 0.65]] D: [[0.089, -0.712, 0.114, 5.287, 4.148, 0.629]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_131_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_131_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.917, -0.639, 0.621, 0.336, 6.104, 1.183], [0.361, -2.884, 0.637, 5.668, -0.024, 1.879], [-2.761, -1.433, 0.573, -0.228, 0.551, 1.578], [-3.018, -2.023, 1.21, 0.696, 0.033, 1.511], [-2.944, 0.173, 0.693, 0.375, 4.326, 1.889]] B: [[2.88, 0.258, 0.921, 0.635, 5.466, 1.974], [-0.061, -2.646, 0.552, 6.114, -0.006, 1.775], [-3.069, -1.6, 0.804, 0.521, 0.433, 1.489], [-3.084, -1.953, 1.232, 0.742, 0.11, 1.43], [-2.84, 1.121, 0.562, 0.204, 4.902, 1.824]] C: [[3.129, -0.248, 1.092, 0.28, 6.006, 1.69], [0.277, -3.248, 1.229, 5.639, 0.457, 1.83], [-2.943, -1.702, 1.206, 0.61, 0.818, 1.511], [-2.632, -1.423, 0.42, 0.373, 0.138, 1.635], [-3.02, 0.349, 0.427, 0.566, 4.15, 1.781]] D: [[3.003, -0.173, 0.772, 0.324, 5.743, 1.505], [-0.052, -3.097, 0.827, 6.005, 0.286, 1.553], [-3.164, -1.839, 0.77, 0.192, 0.577, 1.362], [-2.872, -1.562, 0.743, 0.498, 0.153, 1.361], [-2.619, 0.636, 0.832, 0.279, 4.454, 1.688]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.924593, 0.219455, -0.311397], [0.371095, 0.334047, -0.86643], [-0.086121, -0.916653, -0.390296]]; the translation vector: [7.650298, 2.745242, 1.444521], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[2.917, -0.639, 0.621, 0.336, 6.104, 1.183], [0.361, -2.884, 0.637, 5.668, -0.024, 1.879], [-2.761, -1.433, 0.573, -0.228, 0.551, 1.578], [-3.018, -2.023, 1.21, 0.696, 0.033, 1.511], [-2.944, 0.173, 0.693, 0.375, 4.326, 1.889]] B: [[2.88, 0.258, 0.921, 0.635, 5.466, 1.974], [-0.061, -2.646, 0.552, 6.114, -0.006, 1.775], [-3.069, -1.6, 0.804, 0.521, 0.433, 1.489], [-3.084, -1.953, 1.232, 0.742, 0.11, 1.43], [-2.84, 1.121, 0.562, 0.204, 4.902, 1.824]] C: [[3.129, -0.248, 1.092, 0.28, 6.006, 1.69], [0.277, -3.248, 1.229, 5.639, 0.457, 1.83], [-2.943, -1.702, 1.206, 0.61, 0.818, 1.511], [-2.632, -1.423, 0.42, 0.373, 0.138, 1.635], [-3.02, 0.349, 0.427, 0.566, 4.15, 1.781]] D: [[3.003, -0.173, 0.772, 0.324, 5.743, 1.505], [-0.052, -3.097, 0.827, 6.005, 0.286, 1.553], [-3.164, -1.839, 0.77, 0.192, 0.577, 1.362], [-2.872, -1.562, 0.743, 0.498, 0.153, 1.361], [-2.619, 0.636, 0.832, 0.279, 4.454, 1.688]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_132_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_132_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.133, 0.902, 0.422, 0.039, 0.22, 0.632]] B: [[-0.076, 0.973, 0.415, -0.004, 1.174, 1.248]] C: [[0.144, 0.321, 0.705, -0.021, 0.284, 1.035]] D: [[0.355, 0.535, 0.346, 0.07, 0.677, 0.805]]
Given a RGB image and a depth image, please detect the 3D bounding box of the dishwasher in the scene. The camera pose information includes: the rotation matrix: [[0.975982, 0.033782, -0.215214], [0.215389, -0.297687, 0.930048], [-0.032648, -0.954066, -0.297814]]; the translation vector: [2.838751, 1.414222, 1.664536], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.133, 0.902, 0.422, 0.039, 0.22, 0.632]] B: [[-0.076, 0.973, 0.415, -0.004, 1.174, 1.248]] C: [[0.144, 0.321, 0.705, -0.021, 0.284, 1.035]] D: [[0.355, 0.535, 0.346, 0.07, 0.677, 0.805]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_133_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_133_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.578, -0.219, 1.033, 0.257, 3.748, 1.935], [2.209, 0.671, 0.788, -0.095, 3.689, 2.508], [0.223, -2.291, 0.584, 0.625, 0.246, 1.596], [0.409, -2.777, 1.049, -0.283, 0.131, 1.81]] B: [[-2.04, 0.586, 0.772, 0.304, 3.812, 1.848], [1.619, 0.488, 0.655, 0.555, 3.765, 1.94], [0.355, -2.984, 1.136, -0.107, 0.055, 1.74], [0.752, -2.78, 0.749, 0.33, 0.188, 1.815]] C: [[-1.581, 0.188, 1.09, 0.283, 3.526, 2.183], [1.935, 0.185, 1.045, 0.157, 3.57, 2.128], [0.384, -2.556, 0.863, 0.244, 0.135, 1.758], [0.278, -2.37, 1.022, 0.1, 0.539, 2.045]] D: [[-1.492, -0.235, 1.434, 0.171, 3.146, 1.819], [2.128, 0.651, 1.233, 0.526, 3.819, 1.664], [0.295, -2.822, 1.218, -0.087, 0.184, 1.532], [0.45, -1.956, 1.009, 0.299, 0.644, 2.242]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.037281, 0.595041, -0.80283], [0.998378, -0.012419, -0.055566], [-0.043034, -0.803599, -0.593613]]; the translation vector: [3.95675, 2.244474, 1.442954], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.578, -0.219, 1.033, 0.257, 3.748, 1.935], [2.209, 0.671, 0.788, -0.095, 3.689, 2.508], [0.223, -2.291, 0.584, 0.625, 0.246, 1.596], [0.409, -2.777, 1.049, -0.283, 0.131, 1.81]] B: [[-2.04, 0.586, 0.772, 0.304, 3.812, 1.848], [1.619, 0.488, 0.655, 0.555, 3.765, 1.94], [0.355, -2.984, 1.136, -0.107, 0.055, 1.74], [0.752, -2.78, 0.749, 0.33, 0.188, 1.815]] C: [[-1.581, 0.188, 1.09, 0.283, 3.526, 2.183], [1.935, 0.185, 1.045, 0.157, 3.57, 2.128], [0.384, -2.556, 0.863, 0.244, 0.135, 1.758], [0.278, -2.37, 1.022, 0.1, 0.539, 2.045]] D: [[-1.492, -0.235, 1.434, 0.171, 3.146, 1.819], [2.128, 0.651, 1.233, 0.526, 3.819, 1.664], [0.295, -2.822, 1.218, -0.087, 0.184, 1.532], [0.45, -1.956, 1.009, 0.299, 0.644, 2.242]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_134_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_134_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.199, 1.125, 0.399, 0.214, 0.05, 0.589]] B: [[0.02, 1.322, 0.476, 0.689, 0.454, 0.768]] C: [[0.504, 0.831, 0.74, 0.202, 0.254, 0.39]] D: [[0.93, 1.224, 1.103, 0.115, -0.143, 0.862]]
Given a RGB image and a depth image, please detect the 3D bounding box of the shelf in the scene. The camera pose information includes: the rotation matrix: [[0.994446, -0.078697, 0.06988], [-0.104992, -0.787844, 0.606859], [0.007297, -0.610826, -0.791731]]; the translation vector: [1.305105, 0.510448, 1.183315], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.199, 1.125, 0.399, 0.214, 0.05, 0.589]] B: [[0.02, 1.322, 0.476, 0.689, 0.454, 0.768]] C: [[0.504, 0.831, 0.74, 0.202, 0.254, 0.39]] D: [[0.93, 1.224, 1.103, 0.115, -0.143, 0.862]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_135_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_135_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.403, 0.709, 0.086, 0.284, 0.032, 0.061]] B: [[1.358, 0.357, -0.003, 0.163, 0.142, 0.021]] C: [[1.451, 0.553, 0.13, 0.387, 0.236, 0.338]] D: [[1.592, 0.722, 0.492, 0.54, 0.067, 0.402]]
Given a RGB image and a depth image, please detect the 3D bounding box of the trash can in the scene. The camera pose information includes: the rotation matrix: [[-0.573389, -0.355745, 0.738018], [-0.818965, 0.223754, -0.528424], [0.02285, -0.907403, -0.419641]]; the translation vector: [2.061407, 3.857203, 1.382209], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.403, 0.709, 0.086, 0.284, 0.032, 0.061]] B: [[1.358, 0.357, -0.003, 0.163, 0.142, 0.021]] C: [[1.451, 0.553, 0.13, 0.387, 0.236, 0.338]] D: [[1.592, 0.722, 0.492, 0.54, 0.067, 0.402]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_136_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_136_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.019, 1.716, -0.199, 0.133, 0.443, 0.08]] B: [[1.539, 1.317, 0.169, 1.021, 0.789, 0.672]] C: [[1.691, 1.543, 0.248, 0.524, 0.565, 0.475]] D: [[1.676, 1.663, -0.114, 0.76, 0.881, 0.004]]
Given a RGB image and a depth image, please detect the 3D bounding box of the footrest in the scene. The camera pose information includes: the rotation matrix: [[-0.752388, 0.33007, -0.570058], [0.655329, 0.287372, -0.698542], [-0.066749, -0.89915, -0.43252]]; the translation vector: [3.814293, 2.583141, 1.394159], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[2.019, 1.716, -0.199, 0.133, 0.443, 0.08]] B: [[1.539, 1.317, 0.169, 1.021, 0.789, 0.672]] C: [[1.691, 1.543, 0.248, 0.524, 0.565, 0.475]] D: [[1.676, 1.663, -0.114, 0.76, 0.881, 0.004]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_137_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_137_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.123, 1.117, 1.321, 0.743, 0.381, 0.635], [2.682, 1.29, 0.828, 0.463, 1.156, 0.705], [2.834, 1.547, 0.399, 0.032, 0.368, 0.16], [3.096, 0.047, 0.87, -0.078, 0.326, -0.125], [2.563, 0.993, 1.356, 0.811, 0.73, 0.229], [2.143, 0.969, 1.037, 0.642, 1.052, 0.055], [2.659, -0.615, 0.836, 0.248, 1.054, 0.022], [3.223, -0.649, 1.168, 0.253, 1.288, 0.671], [2.454, -0.393, 0.682, 0.657, 1.137, 0.691], [-3.644, 1.213, 1.46, 0.605, 1.274, 0.706], [-3.657, -0.185, 0.669, 0.323, 1.16, 0.8], [-3.228, -0.103, 1.329, 0.441, 0.997, 0.754], [-3.305, 0.306, 0.543, 0.056, 1.942, 0.326], [-3.554, -0.503, 0.414, 0.642, 0.665, 0.745], [-2.947, -0.695, 0.368, 0.59, 0.436, 0.372], [-3.593, -0.106, 0.806, 0.216, 0.592, 0.301]] B: [[2.989, 1.126, 0.794, -0.179, 0.245, 0.369], [2.962, 1.061, 0.623, -0.057, 0.36, 0.431], [2.845, 1.185, 0.945, 0.308, 0.535, 0.574], [2.424, 0.962, 1.637, -0.272, 0.494, 0.77], [3.085, 0.394, 0.93, 0.245, 0.901, 0.482], [2.87, 0.321, 0.254, 0.308, 0.264, 0.679], [2.834, -0.509, 1.34, 0.641, 0.49, 0.271], [2.993, -0.295, 0.769, -0.075, 1.002, 0.589], [3.132, -0.129, 0.78, 0.069, 1.025, 0.007], [-2.917, 1.638, 1.353, 0.35, 0.736, 0.591], [-2.828, -0.168, 1.186, 0.057, 1.347, 0.51], [-3.297, -0.456, 0.362, 0.307, 0.654, 0.781], [-3.301, 0.612, 0.703, 0.328, 1.414, 0.306], [-2.89, -0.213, 0.298, -0.086, 1.058, 0.488], [-2.855, -0.016, -0.219, -0.168, 0.422, -0.035], [-3.555, 0.252, 0.516, -0.109, 1.029, 0.664]] C: [[2.568, 1.418, 1.271, 0.257, 0.709, 0.306], [2.646, 1.448, 0.95, 0.305, 0.76, 0.302], [2.592, 1.461, 0.636, 0.212, 0.718, 0.28], [2.65, 0.514, 1.213, 0.222, 0.814, 0.309], [2.738, 0.497, 0.888, 0.381, 0.863, 0.308], [2.639, 0.563, 0.627, 0.305, 0.736, 0.188], [2.693, -0.392, 1.14, 0.281, 0.891, 0.334], [2.727, -0.372, 0.833, 0.29, 0.926, 0.3], [2.691, -0.383, 0.563, 0.264, 0.854, 0.201], [-3.22, 1.231, 1.017, 0.313, 0.915, 0.346], [-3.273, 0.289, 0.923, 0.23, 1.204, 0.355], [-3.222, -0.487, 0.833, 0.334, 0.747, 0.368], [-3.341, 0.627, 0.626, 0.449, 1.466, 0.437], [-3.265, -0.411, 0.526, 0.337, 0.641, 0.343], [-3.203, -0.328, 0.27, 0.175, 0.592, 0.204], [-3.277, 0.365, 0.338, 0.332, 0.934, 0.242]] D: [[2.244, 1.249, 1.196, 0.59, 0.671, 0.591], [3.002, 1.584, 0.459, 0.732, 0.625, -0.064], [2.803, 1.399, 0.195, 0.554, 0.24, -0.185], [2.948, 0.428, 1.564, 0.649, 0.642, 0.076], [2.502, 0.944, 1.279, 0.724, 1.079, 0.788], [3.063, 0.247, 0.912, 0.247, 0.578, 0.126], [2.848, -0.809, 0.778, 0.441, 1.15, 0.263], [2.483, -0.756, 0.605, 0.63, 1.407, 0.292], [2.369, -0.586, 0.732, 0.348, 0.461, 0.12], [-3.238, 0.78, 0.778, 0.212, 1.143, -0.102], [-3.116, 0.426, 0.879, 0.248, 1.646, 0.306], [-2.875, -0.393, 1.087, 0.035, 1.245, 0.038], [-3.308, 0.845, 1.118, 0.472, 1.582, 0.109], [-3.33, -0.848, 0.583, 0.088, 1.108, -0.004], [-3.371, -0.081, 0.236, -0.02, 0.647, 0.543], [-3.267, -0.114, -0.13, -0.134, 1.197, -0.109]]
Given a RGB image and a depth image, please detect the 3D bounding box of the books in the scene. The camera pose information includes: the rotation matrix: [[0.892065, -0.360019, 0.273141], [-0.443019, -0.577417, 0.685801], [-0.089185, -0.732786, -0.674589]]; the translation vector: [2.898737, 2.45906, 1.649541], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[2.123, 1.117, 1.321, 0.743, 0.381, 0.635], [2.682, 1.29, 0.828, 0.463, 1.156, 0.705], [2.834, 1.547, 0.399, 0.032, 0.368, 0.16], [3.096, 0.047, 0.87, -0.078, 0.326, -0.125], [2.563, 0.993, 1.356, 0.811, 0.73, 0.229], [2.143, 0.969, 1.037, 0.642, 1.052, 0.055], [2.659, -0.615, 0.836, 0.248, 1.054, 0.022], [3.223, -0.649, 1.168, 0.253, 1.288, 0.671], [2.454, -0.393, 0.682, 0.657, 1.137, 0.691], [-3.644, 1.213, 1.46, 0.605, 1.274, 0.706], [-3.657, -0.185, 0.669, 0.323, 1.16, 0.8], [-3.228, -0.103, 1.329, 0.441, 0.997, 0.754], [-3.305, 0.306, 0.543, 0.056, 1.942, 0.326], [-3.554, -0.503, 0.414, 0.642, 0.665, 0.745], [-2.947, -0.695, 0.368, 0.59, 0.436, 0.372], [-3.593, -0.106, 0.806, 0.216, 0.592, 0.301]] B: [[2.989, 1.126, 0.794, -0.179, 0.245, 0.369], [2.962, 1.061, 0.623, -0.057, 0.36, 0.431], [2.845, 1.185, 0.945, 0.308, 0.535, 0.574], [2.424, 0.962, 1.637, -0.272, 0.494, 0.77], [3.085, 0.394, 0.93, 0.245, 0.901, 0.482], [2.87, 0.321, 0.254, 0.308, 0.264, 0.679], [2.834, -0.509, 1.34, 0.641, 0.49, 0.271], [2.993, -0.295, 0.769, -0.075, 1.002, 0.589], [3.132, -0.129, 0.78, 0.069, 1.025, 0.007], [-2.917, 1.638, 1.353, 0.35, 0.736, 0.591], [-2.828, -0.168, 1.186, 0.057, 1.347, 0.51], [-3.297, -0.456, 0.362, 0.307, 0.654, 0.781], [-3.301, 0.612, 0.703, 0.328, 1.414, 0.306], [-2.89, -0.213, 0.298, -0.086, 1.058, 0.488], [-2.855, -0.016, -0.219, -0.168, 0.422, -0.035], [-3.555, 0.252, 0.516, -0.109, 1.029, 0.664]] C: [[2.568, 1.418, 1.271, 0.257, 0.709, 0.306], [2.646, 1.448, 0.95, 0.305, 0.76, 0.302], [2.592, 1.461, 0.636, 0.212, 0.718, 0.28], [2.65, 0.514, 1.213, 0.222, 0.814, 0.309], [2.738, 0.497, 0.888, 0.381, 0.863, 0.308], [2.639, 0.563, 0.627, 0.305, 0.736, 0.188], [2.693, -0.392, 1.14, 0.281, 0.891, 0.334], [2.727, -0.372, 0.833, 0.29, 0.926, 0.3], [2.691, -0.383, 0.563, 0.264, 0.854, 0.201], [-3.22, 1.231, 1.017, 0.313, 0.915, 0.346], [-3.273, 0.289, 0.923, 0.23, 1.204, 0.355], [-3.222, -0.487, 0.833, 0.334, 0.747, 0.368], [-3.341, 0.627, 0.626, 0.449, 1.466, 0.437], [-3.265, -0.411, 0.526, 0.337, 0.641, 0.343], [-3.203, -0.328, 0.27, 0.175, 0.592, 0.204], [-3.277, 0.365, 0.338, 0.332, 0.934, 0.242]] D: [[2.244, 1.249, 1.196, 0.59, 0.671, 0.591], [3.002, 1.584, 0.459, 0.732, 0.625, -0.064], [2.803, 1.399, 0.195, 0.554, 0.24, -0.185], [2.948, 0.428, 1.564, 0.649, 0.642, 0.076], [2.502, 0.944, 1.279, 0.724, 1.079, 0.788], [3.063, 0.247, 0.912, 0.247, 0.578, 0.126], [2.848, -0.809, 0.778, 0.441, 1.15, 0.263], [2.483, -0.756, 0.605, 0.63, 1.407, 0.292], [2.369, -0.586, 0.732, 0.348, 0.461, 0.12], [-3.238, 0.78, 0.778, 0.212, 1.143, -0.102], [-3.116, 0.426, 0.879, 0.248, 1.646, 0.306], [-2.875, -0.393, 1.087, 0.035, 1.245, 0.038], [-3.308, 0.845, 1.118, 0.472, 1.582, 0.109], [-3.33, -0.848, 0.583, 0.088, 1.108, -0.004], [-3.371, -0.081, 0.236, -0.02, 0.647, 0.543], [-3.267, -0.114, -0.13, -0.134, 1.197, -0.109]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_138_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_138_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.568, 1.594, 2.336, 3.002, 0.215, 1.78], [-1.527, -0.451, 1.258, 0.103, 4.121, 1.756], [-1.386, -2.636, 1.043, -0.207, -0.22, 1.193], [1.834, 0.934, 1.595, 0.321, 1.764, 2.84], [1.018, -0.319, 0.583, 1.01, 0.681, 1.687]] B: [[0.072, 1.537, 1.845, 2.689, 0.191, 1.622], [-1.273, -0.316, 0.956, 0.156, 3.767, 1.891], [-1.14, -2.18, 0.679, 0.246, 0.067, 1.34], [1.381, 0.651, 1.354, 0.135, 1.692, 2.602], [0.889, -0.737, 0.87, 1.059, 1.122, 1.773]] C: [[0.21, 1.662, 1.825, 2.75, -0.252, 2.024], [-1.56, -0.058, 0.561, 0.054, 3.741, 2.333], [-1.055, -2.665, 0.535, 0.196, 0.05, 1.825], [1.164, 0.58, 1.628, 0.045, 1.482, 2.195], [1.198, -0.291, 1.331, 0.727, 1.34, 1.309]] D: [[-0.147, 1.793, 1.85, 3.103, 0.596, 1.69], [-1.538, -0.388, 0.463, 0.445, 3.441, 1.475], [-1.625, -1.946, 0.934, 0.072, -0.182, 1.409], [1.247, 1.123, 0.994, 0.033, 1.379, 2.521], [0.847, -0.38, 0.424, 0.888, 1.469, 2.148]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.721847, -0.019511, -0.691778], [0.690918, -0.036893, 0.721991], [-0.039608, -0.999129, -0.013151]]; the translation vector: [1.871862, 0.815296, 1.594356], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.568, 1.594, 2.336, 3.002, 0.215, 1.78], [-1.527, -0.451, 1.258, 0.103, 4.121, 1.756], [-1.386, -2.636, 1.043, -0.207, -0.22, 1.193], [1.834, 0.934, 1.595, 0.321, 1.764, 2.84], [1.018, -0.319, 0.583, 1.01, 0.681, 1.687]] B: [[0.072, 1.537, 1.845, 2.689, 0.191, 1.622], [-1.273, -0.316, 0.956, 0.156, 3.767, 1.891], [-1.14, -2.18, 0.679, 0.246, 0.067, 1.34], [1.381, 0.651, 1.354, 0.135, 1.692, 2.602], [0.889, -0.737, 0.87, 1.059, 1.122, 1.773]] C: [[0.21, 1.662, 1.825, 2.75, -0.252, 2.024], [-1.56, -0.058, 0.561, 0.054, 3.741, 2.333], [-1.055, -2.665, 0.535, 0.196, 0.05, 1.825], [1.164, 0.58, 1.628, 0.045, 1.482, 2.195], [1.198, -0.291, 1.331, 0.727, 1.34, 1.309]] D: [[-0.147, 1.793, 1.85, 3.103, 0.596, 1.69], [-1.538, -0.388, 0.463, 0.445, 3.441, 1.475], [-1.625, -1.946, 0.934, 0.072, -0.182, 1.409], [1.247, 1.123, 0.994, 0.033, 1.379, 2.521], [0.847, -0.38, 0.424, 0.888, 1.469, 2.148]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_139_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_139_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.013, -1.238, 0.461, 0.493, 0.288, 0.575], [-1.147, 3.348, 0.377, 0.564, 1.212, 0.508], [0.233, -3.522, 0.086, 0.938, 1.233, 0.371], [1.742, -2.531, 0.357, 1.04, 1.008, 0.183], [-0.823, -2.335, 0.1, 1.256, 0.934, 0.241], [-1.592, 0.953, 0.372, 1.131, 0.478, 0.788], [-0.027, 4.368, 1.235, 0.272, -0.107, 0.356], [2.853, 3.344, 0.339, 0.665, 0.157, 0.567], [2.027, 4.048, 1.116, 0.515, 0.345, 0.52], [0.87, 3.839, 0.8, 0.696, -0.287, 0.501], [1.369, 2.326, 0.538, 0.245, 0.786, 0.243], [0.357, 3.043, 0.662, 0.778, 0.111, 0.513], [1.447, 2.656, 0.359, 0.141, 0.33, 0.84]] B: [[0.068, -1.042, 0.544, 0.886, 0.779, 0.545], [-1.479, 3.034, 0.552, 0.898, 0.801, 0.497], [-0.06, -3.112, 0.543, 0.84, 0.784, 0.511], [1.274, -2.138, 0.543, 0.738, 0.855, 0.547], [-0.786, -2.2, 0.536, 0.806, 0.879, 0.474], [-1.39, 1.148, 0.549, 0.822, 0.745, 0.54], [0.444, 4.003, 0.791, 0.485, 0.139, 0.082], [2.511, 3.843, 0.762, 0.448, 0.131, 0.083], [1.884, 3.916, 0.775, 0.46, 0.149, 0.083], [1.153, 3.946, 0.791, 0.453, 0.166, 0.098], [1.053, 2.651, 0.606, 0.523, 0.61, 0.485], [0.449, 2.899, 0.606, 0.476, 0.557, 0.467], [1.688, 2.596, 0.605, 0.503, 0.592, 0.451]] C: [[0.102, -0.947, 0.484, 1.245, 0.79, 0.775], [-1.118, 3.375, 0.842, 0.401, 1.069, 0.196], [0.407, -2.782, 0.934, 1.07, 0.467, 0.067], [1.541, -2.237, 0.403, 0.888, 1.246, 0.245], [-0.917, -1.889, 0.628, 0.956, 1.204, 0.523], [-1.021, 1.176, 0.814, 0.368, 0.456, 0.678], [0.573, 4.084, 1.228, 0.815, 0.355, 0.385], [2.848, 3.659, 0.488, 0.047, 0.047, 0.092], [1.907, 4.123, 0.733, 0.026, 0.33, -0.009], [1.212, 4.443, 1.139, 0.078, -0.234, 0.21], [0.892, 2.632, 1.105, 0.392, 1.061, 0.435], [0.166, 3.349, 0.352, 0.282, 0.481, 0.755], [1.529, 2.634, 0.397, 0.324, 0.54, 0.072]] D: [[-0.194, -1.122, 0.104, 1.378, 1.12, 0.253], [-1.005, 3.518, 0.745, 0.428, 0.792, 0.08], [0.214, -2.901, 0.412, 0.728, 0.43, 0.91], [1.573, -2.219, 0.557, 0.934, 1.13, 0.876], [-0.782, -2.154, 0.858, 0.543, 1.135, 0.108], [-1.448, 1.097, 0.92, 1.197, 0.497, 0.181], [0.045, 3.571, 0.423, 0.736, -0.143, -0.417], [2.244, 4.297, 0.746, 0.101, 0.473, -0.26], [1.879, 3.692, 0.375, 0.596, -0.051, -0.206], [1.372, 4.096, 0.929, 0.827, -0.125, 0.334], [1.326, 2.984, 0.19, 0.493, 0.248, 0.576], [0.74, 2.996, 0.477, 0.655, 0.254, 0.849], [2.003, 3.037, 0.818, 0.844, 0.675, 0.272]]
Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[0.853196, -0.330732, 0.403328], [-0.517406, -0.438892, 0.734619], [-0.065945, -0.835458, -0.545584]]; the translation vector: [2.734716, 6.775187, 1.412962], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.013, -1.238, 0.461, 0.493, 0.288, 0.575], [-1.147, 3.348, 0.377, 0.564, 1.212, 0.508], [0.233, -3.522, 0.086, 0.938, 1.233, 0.371], [1.742, -2.531, 0.357, 1.04, 1.008, 0.183], [-0.823, -2.335, 0.1, 1.256, 0.934, 0.241], [-1.592, 0.953, 0.372, 1.131, 0.478, 0.788], [-0.027, 4.368, 1.235, 0.272, -0.107, 0.356], [2.853, 3.344, 0.339, 0.665, 0.157, 0.567], [2.027, 4.048, 1.116, 0.515, 0.345, 0.52], [0.87, 3.839, 0.8, 0.696, -0.287, 0.501], [1.369, 2.326, 0.538, 0.245, 0.786, 0.243], [0.357, 3.043, 0.662, 0.778, 0.111, 0.513], [1.447, 2.656, 0.359, 0.141, 0.33, 0.84]] B: [[0.068, -1.042, 0.544, 0.886, 0.779, 0.545], [-1.479, 3.034, 0.552, 0.898, 0.801, 0.497], [-0.06, -3.112, 0.543, 0.84, 0.784, 0.511], [1.274, -2.138, 0.543, 0.738, 0.855, 0.547], [-0.786, -2.2, 0.536, 0.806, 0.879, 0.474], [-1.39, 1.148, 0.549, 0.822, 0.745, 0.54], [0.444, 4.003, 0.791, 0.485, 0.139, 0.082], [2.511, 3.843, 0.762, 0.448, 0.131, 0.083], [1.884, 3.916, 0.775, 0.46, 0.149, 0.083], [1.153, 3.946, 0.791, 0.453, 0.166, 0.098], [1.053, 2.651, 0.606, 0.523, 0.61, 0.485], [0.449, 2.899, 0.606, 0.476, 0.557, 0.467], [1.688, 2.596, 0.605, 0.503, 0.592, 0.451]] C: [[0.102, -0.947, 0.484, 1.245, 0.79, 0.775], [-1.118, 3.375, 0.842, 0.401, 1.069, 0.196], [0.407, -2.782, 0.934, 1.07, 0.467, 0.067], [1.541, -2.237, 0.403, 0.888, 1.246, 0.245], [-0.917, -1.889, 0.628, 0.956, 1.204, 0.523], [-1.021, 1.176, 0.814, 0.368, 0.456, 0.678], [0.573, 4.084, 1.228, 0.815, 0.355, 0.385], [2.848, 3.659, 0.488, 0.047, 0.047, 0.092], [1.907, 4.123, 0.733, 0.026, 0.33, -0.009], [1.212, 4.443, 1.139, 0.078, -0.234, 0.21], [0.892, 2.632, 1.105, 0.392, 1.061, 0.435], [0.166, 3.349, 0.352, 0.282, 0.481, 0.755], [1.529, 2.634, 0.397, 0.324, 0.54, 0.072]] D: [[-0.194, -1.122, 0.104, 1.378, 1.12, 0.253], [-1.005, 3.518, 0.745, 0.428, 0.792, 0.08], [0.214, -2.901, 0.412, 0.728, 0.43, 0.91], [1.573, -2.219, 0.557, 0.934, 1.13, 0.876], [-0.782, -2.154, 0.858, 0.543, 1.135, 0.108], [-1.448, 1.097, 0.92, 1.197, 0.497, 0.181], [0.045, 3.571, 0.423, 0.736, -0.143, -0.417], [2.244, 4.297, 0.746, 0.101, 0.473, -0.26], [1.879, 3.692, 0.375, 0.596, -0.051, -0.206], [1.372, 4.096, 0.929, 0.827, -0.125, 0.334], [1.326, 2.984, 0.19, 0.493, 0.248, 0.576], [0.74, 2.996, 0.477, 0.655, 0.254, 0.849], [2.003, 3.037, 0.818, 0.844, 0.675, 0.272]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_140_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_140_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.478, -1.621, 1.471, 0.04, 0.607, 0.77], [-0.622, -0.28, 0.778, 0.596, 0.791, 0.172], [0.68, -2.333, 1.441, 0.527, 0.774, 0.878], [0.47, -3.455, 1.236, 0.145, 0.605, 0.702], [-1.07, -2.607, 1.289, 0.421, 0.201, 0.117], [-0.819, -3.811, 1.501, 0.378, 0.459, 0.305], [-0.289, -1.598, 0.306, 0.193, 0.374, 1.351], [-0.144, -0.28, 1.064, 0.516, 0.462, 1.314], [-0.472, 1.134, 0.95, 0.612, 0.425, 0.242], [0.292, 1.559, -0.0, 1.024, 0.739, 0.637], [1.632, 1.532, 0.377, 0.961, 0.147, 0.54], [1.253, 1.503, 0.223, 0.356, 0.173, 0.917], [2.079, 0.639, 0.524, 0.497, 0.63, 1.101], [1.452, -0.032, 0.35, 1.029, 0.429, 0.469], [1.964, -1.067, 0.351, 1.202, 1.067, 0.649], [1.915, -1.339, 0.962, 0.392, 0.481, -0.02]] B: [[-1.05, -1.003, 1.329, 0.32, 0.076, 0.616], [-0.594, -0.426, 0.767, 0.622, 0.307, 0.007], [0.602, -2.305, 1.043, 0.218, 0.243, 0.681], [0.924, -3.409, 0.98, 0.773, 0.471, 1.089], [-0.329, -2.354, 0.789, 0.408, 0.875, 0.623], [-0.349, -3.787, 1.449, 0.31, 0.976, 0.266], [0.652, -1.018, 1.006, 0.796, 0.883, 0.697], [0.628, -0.604, 0.772, 0.114, 0.996, 0.953], [-1.118, 1.128, 0.061, 0.216, 0.338, 0.764], [0.65, 1.585, 0.323, 0.699, 0.859, 0.499], [1.631, 1.493, 0.088, 1.244, 0.636, 1.121], [1.187, 0.927, 0.824, 0.22, 0.275, 0.894], [1.693, 0.178, 0.2, 0.357, 0.96, 0.555], [1.798, -0.426, 0.556, 0.111, 1.016, 0.592], [1.891, -0.692, 0.467, 0.91, 1.42, 0.916], [1.538, -2.029, 0.941, 0.82, 1.037, 0.527]] C: [[-0.797, -1.314, 1.076, 0.174, 0.538, 0.297], [-0.804, -0.643, 0.993, 0.18, 0.483, 0.317], [0.265, -2.771, 0.976, 0.564, 0.483, 0.724], [0.443, -3.263, 1.105, 0.404, 0.755, 0.654], [-0.786, -2.701, 1.224, 0.235, 0.623, 0.423], [-0.579, -3.467, 1.386, 0.149, 0.491, 0.284], [0.195, -1.173, 0.617, 0.439, 0.594, 0.981], [0.152, -0.693, 0.576, 0.363, 0.648, 0.901], [-0.836, 1.438, 0.551, 0.438, 0.598, 0.552], [0.258, 1.345, 0.466, 0.561, 0.507, 0.736], [1.246, 1.609, 0.396, 0.752, 0.566, 0.883], [1.646, 1.19, 0.575, 0.611, 0.592, 0.619], [1.73, 0.493, 0.521, 0.445, 0.583, 0.771], [1.766, -0.179, 0.551, 0.536, 0.58, 0.774], [1.864, -0.697, 0.533, 0.816, 1.199, 0.994], [1.74, -1.667, 0.652, 0.516, 0.607, 0.36]] D: [[-0.49, -1.289, 0.9, 0.491, 0.951, 0.59], [-1.107, -1.021, 1.479, 0.523, 0.505, 0.09], [-0.233, -2.971, 1.208, 0.309, 0.946, 0.617], [0.587, -2.842, 0.811, 0.828, 0.821, 0.621], [-0.674, -2.976, 1.257, -0.139, 0.206, 0.639], [-0.269, -3.606, 1.299, -0.169, 0.133, 0.486], [0.033, -0.697, 1.063, 0.567, 1.022, 1.265], [0.252, -0.714, 0.426, 0.514, 0.322, 1.359], [-1.161, 1.486, 0.647, 0.683, 0.314, 0.187], [-0.11, 1.173, 0.725, 0.462, 0.264, 1.138], [1.341, 1.682, 0.277, 0.312, 0.356, 0.94], [1.815, 1.188, 0.624, 1.015, 0.174, 0.508], [1.714, 0.423, 0.79, 0.889, 0.659, 0.533], [1.648, -0.367, 0.718, 0.468, 1.049, 0.941], [2.335, -0.44, 0.71, 1.148, 1.407, 0.783], [1.632, -1.945, 0.223, 0.453, 0.239, 0.703]]
Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.476704, 0.41796, -0.773345], [0.878176, 0.186897, -0.440314], [-0.039498, -0.889033, -0.456137]]; the translation vector: [2.405627, 4.675593, 1.276166], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.478, -1.621, 1.471, 0.04, 0.607, 0.77], [-0.622, -0.28, 0.778, 0.596, 0.791, 0.172], [0.68, -2.333, 1.441, 0.527, 0.774, 0.878], [0.47, -3.455, 1.236, 0.145, 0.605, 0.702], [-1.07, -2.607, 1.289, 0.421, 0.201, 0.117], [-0.819, -3.811, 1.501, 0.378, 0.459, 0.305], [-0.289, -1.598, 0.306, 0.193, 0.374, 1.351], [-0.144, -0.28, 1.064, 0.516, 0.462, 1.314], [-0.472, 1.134, 0.95, 0.612, 0.425, 0.242], [0.292, 1.559, -0.0, 1.024, 0.739, 0.637], [1.632, 1.532, 0.377, 0.961, 0.147, 0.54], [1.253, 1.503, 0.223, 0.356, 0.173, 0.917], [2.079, 0.639, 0.524, 0.497, 0.63, 1.101], [1.452, -0.032, 0.35, 1.029, 0.429, 0.469], [1.964, -1.067, 0.351, 1.202, 1.067, 0.649], [1.915, -1.339, 0.962, 0.392, 0.481, -0.02]] B: [[-1.05, -1.003, 1.329, 0.32, 0.076, 0.616], [-0.594, -0.426, 0.767, 0.622, 0.307, 0.007], [0.602, -2.305, 1.043, 0.218, 0.243, 0.681], [0.924, -3.409, 0.98, 0.773, 0.471, 1.089], [-0.329, -2.354, 0.789, 0.408, 0.875, 0.623], [-0.349, -3.787, 1.449, 0.31, 0.976, 0.266], [0.652, -1.018, 1.006, 0.796, 0.883, 0.697], [0.628, -0.604, 0.772, 0.114, 0.996, 0.953], [-1.118, 1.128, 0.061, 0.216, 0.338, 0.764], [0.65, 1.585, 0.323, 0.699, 0.859, 0.499], [1.631, 1.493, 0.088, 1.244, 0.636, 1.121], [1.187, 0.927, 0.824, 0.22, 0.275, 0.894], [1.693, 0.178, 0.2, 0.357, 0.96, 0.555], [1.798, -0.426, 0.556, 0.111, 1.016, 0.592], [1.891, -0.692, 0.467, 0.91, 1.42, 0.916], [1.538, -2.029, 0.941, 0.82, 1.037, 0.527]] C: [[-0.797, -1.314, 1.076, 0.174, 0.538, 0.297], [-0.804, -0.643, 0.993, 0.18, 0.483, 0.317], [0.265, -2.771, 0.976, 0.564, 0.483, 0.724], [0.443, -3.263, 1.105, 0.404, 0.755, 0.654], [-0.786, -2.701, 1.224, 0.235, 0.623, 0.423], [-0.579, -3.467, 1.386, 0.149, 0.491, 0.284], [0.195, -1.173, 0.617, 0.439, 0.594, 0.981], [0.152, -0.693, 0.576, 0.363, 0.648, 0.901], [-0.836, 1.438, 0.551, 0.438, 0.598, 0.552], [0.258, 1.345, 0.466, 0.561, 0.507, 0.736], [1.246, 1.609, 0.396, 0.752, 0.566, 0.883], [1.646, 1.19, 0.575, 0.611, 0.592, 0.619], [1.73, 0.493, 0.521, 0.445, 0.583, 0.771], [1.766, -0.179, 0.551, 0.536, 0.58, 0.774], [1.864, -0.697, 0.533, 0.816, 1.199, 0.994], [1.74, -1.667, 0.652, 0.516, 0.607, 0.36]] D: [[-0.49, -1.289, 0.9, 0.491, 0.951, 0.59], [-1.107, -1.021, 1.479, 0.523, 0.505, 0.09], [-0.233, -2.971, 1.208, 0.309, 0.946, 0.617], [0.587, -2.842, 0.811, 0.828, 0.821, 0.621], [-0.674, -2.976, 1.257, -0.139, 0.206, 0.639], [-0.269, -3.606, 1.299, -0.169, 0.133, 0.486], [0.033, -0.697, 1.063, 0.567, 1.022, 1.265], [0.252, -0.714, 0.426, 0.514, 0.322, 1.359], [-1.161, 1.486, 0.647, 0.683, 0.314, 0.187], [-0.11, 1.173, 0.725, 0.462, 0.264, 1.138], [1.341, 1.682, 0.277, 0.312, 0.356, 0.94], [1.815, 1.188, 0.624, 1.015, 0.174, 0.508], [1.714, 0.423, 0.79, 0.889, 0.659, 0.533], [1.648, -0.367, 0.718, 0.468, 1.049, 0.941], [2.335, -0.44, 0.71, 1.148, 1.407, 0.783], [1.632, -1.945, 0.223, 0.453, 0.239, 0.703]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_141_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_141_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.214, 2.51, 1.365, 3.041, 0.194, 2.765], [-0.05, -2.478, 0.301, 2.986, 0.3, 0.641], [-1.526, -0.161, 1.336, 0.225, 4.64, 2.734]] B: [[0.048, 2.151, 1.156, 2.76, 0.655, 2.821], [0.225, -2.827, 0.677, 3.049, -0.043, 0.254], [-1.759, -0.568, 1.729, -0.249, 5.02, 2.969]] C: [[0.558, 2.736, 1.619, 3.45, -0.161, 2.854], [-0.367, -2.102, 0.777, 2.594, 0.161, 0.236], [-1.277, -0.254, 1.397, -0.136, 4.615, 2.411]] D: [[0.699, 2.21, 1.721, 3.445, -0.097, 2.767], [0.274, -2.743, -0.017, 2.983, 0.564, 0.816], [-1.467, -0.193, 1.628, 0.718, 4.962, 2.711]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.207785, -0.462455, 0.861952], [-0.977184, 0.13779, -0.161637], [-0.044019, -0.875871, -0.480534]]; the translation vector: [2.720584, 1.654419, 1.522448], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.214, 2.51, 1.365, 3.041, 0.194, 2.765], [-0.05, -2.478, 0.301, 2.986, 0.3, 0.641], [-1.526, -0.161, 1.336, 0.225, 4.64, 2.734]] B: [[0.048, 2.151, 1.156, 2.76, 0.655, 2.821], [0.225, -2.827, 0.677, 3.049, -0.043, 0.254], [-1.759, -0.568, 1.729, -0.249, 5.02, 2.969]] C: [[0.558, 2.736, 1.619, 3.45, -0.161, 2.854], [-0.367, -2.102, 0.777, 2.594, 0.161, 0.236], [-1.277, -0.254, 1.397, -0.136, 4.615, 2.411]] D: [[0.699, 2.21, 1.721, 3.445, -0.097, 2.767], [0.274, -2.743, -0.017, 2.983, 0.564, 0.816], [-1.467, -0.193, 1.628, 0.718, 4.962, 2.711]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_142_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_142_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.781, -0.092, 1.437, 0.297, 5.42, 2.838], [-0.225, -2.203, -0.028, 3.04, -0.15, 0.159], [0.563, 2.457, 1.86, 3.628, 0.174, 3.621], [1.294, -0.516, 1.217, 0.088, 5.292, 2.913], [-1.437, -2.905, 0.867, 0.166, -0.17, 0.831]] B: [[-1.712, -0.169, 1.937, -0.166, 5.172, 3.249], [0.409, -2.556, 0.634, 3.096, 0.671, 0.11], [-0.287, 2.175, 1.704, 3.703, 0.15, 2.806], [2.158, 0.248, 1.0, 0.669, 5.195, 2.453], [-1.117, -2.267, 1.561, 0.31, -0.422, 1.139]] C: [[-1.796, -0.26, 1.071, 0.363, 4.986, 2.747], [-0.333, -2.47, 0.362, 3.532, -0.124, 0.597], [0.208, 2.122, 1.319, 3.656, -0.186, 2.723], [1.521, -0.537, 0.986, 0.704, 5.101, 2.943], [-1.457, -2.856, 0.86, 0.281, 0.313, 0.878]] D: [[-1.474, 0.024, 1.526, 0.216, 4.974, 3.09], [0.118, -2.408, 0.332, 3.201, 0.275, 0.54], [0.144, 2.522, 1.535, 3.347, 0.23, 3.137], [1.788, -0.144, 1.382, 0.213, 5.326, 2.779], [-1.437, -2.464, 1.35, 0.243, 0.036, 0.743]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.45377, -0.425062, 0.783208], [-0.891046, 0.227634, -0.392708], [-0.01136, -0.876074, -0.482043]]; the translation vector: [2.25004, 3.862298, 1.519108], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.781, -0.092, 1.437, 0.297, 5.42, 2.838], [-0.225, -2.203, -0.028, 3.04, -0.15, 0.159], [0.563, 2.457, 1.86, 3.628, 0.174, 3.621], [1.294, -0.516, 1.217, 0.088, 5.292, 2.913], [-1.437, -2.905, 0.867, 0.166, -0.17, 0.831]] B: [[-1.712, -0.169, 1.937, -0.166, 5.172, 3.249], [0.409, -2.556, 0.634, 3.096, 0.671, 0.11], [-0.287, 2.175, 1.704, 3.703, 0.15, 2.806], [2.158, 0.248, 1.0, 0.669, 5.195, 2.453], [-1.117, -2.267, 1.561, 0.31, -0.422, 1.139]] C: [[-1.796, -0.26, 1.071, 0.363, 4.986, 2.747], [-0.333, -2.47, 0.362, 3.532, -0.124, 0.597], [0.208, 2.122, 1.319, 3.656, -0.186, 2.723], [1.521, -0.537, 0.986, 0.704, 5.101, 2.943], [-1.457, -2.856, 0.86, 0.281, 0.313, 0.878]] D: [[-1.474, 0.024, 1.526, 0.216, 4.974, 3.09], [0.118, -2.408, 0.332, 3.201, 0.275, 0.54], [0.144, 2.522, 1.535, 3.347, 0.23, 3.137], [1.788, -0.144, 1.382, 0.213, 5.326, 2.779], [-1.437, -2.464, 1.35, 0.243, 0.036, 0.743]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_143_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_143_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.29, -0.316, 1.432, 0.063, 4.92, 2.21], [-1.382, -1.33, 2.175, 0.695, 0.538, 0.2], [-1.806, -2.363, 0.83, 0.352, 1.114, 1.836], [-1.306, -1.788, 0.815, 0.84, 0.3, 1.933], [-2.082, -0.191, 1.078, 0.269, 3.774, 1.876], [-1.331, 2.183, 1.747, 0.179, -0.216, 1.553], [-1.305, 2.378, 1.485, 0.225, 1.117, 1.988], [0.552, 2.732, 1.097, 2.615, 0.213, 2.449]] B: [[2.019, 0.108, 1.002, 0.215, 5.208, 2.059], [-1.022, -1.729, 2.165, 0.645, 0.146, 0.247], [-1.383, -1.998, 1.17, 0.215, 0.925, 2.24], [-1.526, -1.582, 1.263, 0.348, 0.152, 2.156], [-1.694, 0.207, 1.164, 0.178, 3.686, 2.357], [-1.644, 1.973, 1.343, 0.176, 0.151, 1.146], [-1.605, 2.692, 1.055, 0.124, 1.358, 1.982], [0.625, 2.804, 0.995, 2.8, 0.361, 2.1]] C: [[1.702, 0.103, 1.118, 0.347, 5.169, 2.205], [-0.755, -1.506, 2.319, 1.022, 0.542, -0.064], [-1.248, -1.952, 1.27, 0.08, 1.199, 2.239], [-1.042, -1.657, 1.027, 0.155, -0.197, 2.421], [-1.513, 0.045, 1.167, -0.103, 3.723, 2.465], [-1.23, 1.582, 1.115, -0.014, -0.31, 1.511], [-1.196, 2.213, 1.364, -0.205, 1.046, 1.714], [0.962, 2.867, 0.955, 2.429, 0.313, 2.593]] D: [[2.083, 0.385, 1.347, 0.273, 5.186, 1.86], [-0.546, -1.555, 1.851, 0.975, 0.412, 0.638], [-1.077, -1.883, 1.417, -0.014, 0.602, 2.249], [-1.395, -1.99, 1.177, -0.094, -0.079, 2.003], [-1.5, 0.548, 1.221, 0.453, 3.489, 2.126], [-2.081, 1.694, 1.43, -0.163, 0.443, 1.038], [-1.256, 2.343, 0.839, 0.584, 1.506, 1.621], [0.155, 3.04, 0.757, 2.991, 0.014, 2.136]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.804414, -0.195207, 0.561082], [-0.593456, -0.306943, 0.74404], [0.026978, -0.931494, -0.362756]]; the translation vector: [4.397897, 1.805397, 1.263968], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[2.29, -0.316, 1.432, 0.063, 4.92, 2.21], [-1.382, -1.33, 2.175, 0.695, 0.538, 0.2], [-1.806, -2.363, 0.83, 0.352, 1.114, 1.836], [-1.306, -1.788, 0.815, 0.84, 0.3, 1.933], [-2.082, -0.191, 1.078, 0.269, 3.774, 1.876], [-1.331, 2.183, 1.747, 0.179, -0.216, 1.553], [-1.305, 2.378, 1.485, 0.225, 1.117, 1.988], [0.552, 2.732, 1.097, 2.615, 0.213, 2.449]] B: [[2.019, 0.108, 1.002, 0.215, 5.208, 2.059], [-1.022, -1.729, 2.165, 0.645, 0.146, 0.247], [-1.383, -1.998, 1.17, 0.215, 0.925, 2.24], [-1.526, -1.582, 1.263, 0.348, 0.152, 2.156], [-1.694, 0.207, 1.164, 0.178, 3.686, 2.357], [-1.644, 1.973, 1.343, 0.176, 0.151, 1.146], [-1.605, 2.692, 1.055, 0.124, 1.358, 1.982], [0.625, 2.804, 0.995, 2.8, 0.361, 2.1]] C: [[1.702, 0.103, 1.118, 0.347, 5.169, 2.205], [-0.755, -1.506, 2.319, 1.022, 0.542, -0.064], [-1.248, -1.952, 1.27, 0.08, 1.199, 2.239], [-1.042, -1.657, 1.027, 0.155, -0.197, 2.421], [-1.513, 0.045, 1.167, -0.103, 3.723, 2.465], [-1.23, 1.582, 1.115, -0.014, -0.31, 1.511], [-1.196, 2.213, 1.364, -0.205, 1.046, 1.714], [0.962, 2.867, 0.955, 2.429, 0.313, 2.593]] D: [[2.083, 0.385, 1.347, 0.273, 5.186, 1.86], [-0.546, -1.555, 1.851, 0.975, 0.412, 0.638], [-1.077, -1.883, 1.417, -0.014, 0.602, 2.249], [-1.395, -1.99, 1.177, -0.094, -0.079, 2.003], [-1.5, 0.548, 1.221, 0.453, 3.489, 2.126], [-2.081, 1.694, 1.43, -0.163, 0.443, 1.038], [-1.256, 2.343, 0.839, 0.584, 1.506, 1.621], [0.155, 3.04, 0.757, 2.991, 0.014, 2.136]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_144_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_144_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.219, -0.964, 1.58, 0.354, 3.912, 2.347], [0.255, 0.996, 1.173, 3.495, 1.006, 2.248], [1.513, 0.137, 0.79, 0.63, 3.182, 2.432]] B: [[-1.818, -0.647, 1.066, 0.433, 4.095, 1.902], [0.12, 0.784, 1.447, 3.712, 0.386, 2.623], [1.292, -0.011, 0.89, 0.451, 3.017, 2.105]] C: [[-1.598, -0.539, 1.125, 0.503, 3.791, 2.392], [-0.019, 1.26, 1.209, 3.332, 0.548, 2.478], [1.708, -0.009, 1.196, 0.447, 2.783, 2.468]] D: [[-1.147, -0.143, 1.224, 0.476, 4.202, 2.039], [-0.033, 1.197, 1.039, 3.572, 0.489, 2.65], [1.648, -0.334, 1.403, 0.735, 3.031, 2.541]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.218501, -0.721835, 0.656667], [-0.97193, -0.10083, 0.212566], [-0.087226, -0.684681, -0.723605]]; the translation vector: [2.10902, 2.428258, 1.386435], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.219, -0.964, 1.58, 0.354, 3.912, 2.347], [0.255, 0.996, 1.173, 3.495, 1.006, 2.248], [1.513, 0.137, 0.79, 0.63, 3.182, 2.432]] B: [[-1.818, -0.647, 1.066, 0.433, 4.095, 1.902], [0.12, 0.784, 1.447, 3.712, 0.386, 2.623], [1.292, -0.011, 0.89, 0.451, 3.017, 2.105]] C: [[-1.598, -0.539, 1.125, 0.503, 3.791, 2.392], [-0.019, 1.26, 1.209, 3.332, 0.548, 2.478], [1.708, -0.009, 1.196, 0.447, 2.783, 2.468]] D: [[-1.147, -0.143, 1.224, 0.476, 4.202, 2.039], [-0.033, 1.197, 1.039, 3.572, 0.489, 2.65], [1.648, -0.334, 1.403, 0.735, 3.031, 2.541]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_145_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_145_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.089, 0.93, 0.906, 1.952, 6.847, 0.759], [2.364, 2.183, -0.461, 0.089, -0.064, -0.412], [0.126, -4.445, 0.264, 1.544, 0.593, 0.846], [1.593, -4.523, 0.942, 1.504, 1.198, 0.582]] B: [[0.288, 1.03, -0.052, 1.738, 7.022, 0.872], [3.315, 2.231, -0.328, 0.592, 0.336, -0.023], [0.311, -4.176, 1.057, 1.806, 0.812, 1.384], [1.759, -3.771, 0.974, 2.086, 0.713, 1.164]] C: [[0.167, 0.689, 0.442, 1.571, 6.663, 0.887], [2.849, 2.011, -0.011, 0.132, 0.183, 0.035], [-0.085, -4.074, 0.615, 1.543, 0.713, 0.958], [1.39, -4.168, 0.506, 1.716, 0.715, 0.966]] D: [[0.313, 0.252, 0.284, 1.649, 6.826, 1.244], [2.392, 1.917, -0.34, 0.488, -0.05, 0.218], [0.064, -3.679, 0.658, 2.001, 0.36, 1.007], [1.092, -4.59, 0.839, 1.267, 0.336, 1.034]]
Given a RGB image and a depth image, please detect the 3D bounding box of the table in the scene. The camera pose information includes: the rotation matrix: [[-0.241978, -0.427128, 0.871211], [-0.963615, 0.210861, -0.164264], [-0.113543, -0.879261, -0.462611]]; the translation vector: [2.164319, 10.11033, 1.716674], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.089, 0.93, 0.906, 1.952, 6.847, 0.759], [2.364, 2.183, -0.461, 0.089, -0.064, -0.412], [0.126, -4.445, 0.264, 1.544, 0.593, 0.846], [1.593, -4.523, 0.942, 1.504, 1.198, 0.582]] B: [[0.288, 1.03, -0.052, 1.738, 7.022, 0.872], [3.315, 2.231, -0.328, 0.592, 0.336, -0.023], [0.311, -4.176, 1.057, 1.806, 0.812, 1.384], [1.759, -3.771, 0.974, 2.086, 0.713, 1.164]] C: [[0.167, 0.689, 0.442, 1.571, 6.663, 0.887], [2.849, 2.011, -0.011, 0.132, 0.183, 0.035], [-0.085, -4.074, 0.615, 1.543, 0.713, 0.958], [1.39, -4.168, 0.506, 1.716, 0.715, 0.966]] D: [[0.313, 0.252, 0.284, 1.649, 6.826, 1.244], [2.392, 1.917, -0.34, 0.488, -0.05, 0.218], [0.064, -3.679, 0.658, 2.001, 0.36, 1.007], [1.092, -4.59, 0.839, 1.267, 0.336, 1.034]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_146_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_146_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.766, -1.392, 1.241, 0.359, 0.114, 0.509]] B: [[0.818, -0.933, 0.887, 0.454, 0.574, 0.13]] C: [[0.354, -0.503, 0.874, 0.511, 0.736, 0.517]] D: [[1.154, -1.214, 1.131, 0.407, 0.409, -0.18]]
Given a RGB image and a depth image, please detect the 3D bounding box of the paper cutter in the scene. The camera pose information includes: the rotation matrix: [[0.624751, -0.31057, 0.716403], [-0.780527, -0.273701, 0.562018], [0.021534, -0.910293, -0.413403]]; the translation vector: [-0.212106, 0.775797, 1.619325], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.766, -1.392, 1.241, 0.359, 0.114, 0.509]] B: [[0.818, -0.933, 0.887, 0.454, 0.574, 0.13]] C: [[0.354, -0.503, 0.874, 0.511, 0.736, 0.517]] D: [[1.154, -1.214, 1.131, 0.407, 0.409, -0.18]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_147_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_147_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.354, -1.662, 1.012, 0.018, 0.115, 0.103]] B: [[-0.792, -1.485, 1.441, 0.393, -0.105, 0.505]] C: [[-0.528, -1.745, 1.201, 0.1, 0.492, -0.087]] D: [[-0.815, -1.664, 1.36, -0.019, -0.178, -0.353]]
Given a RGB image and a depth image, please detect the 3D bounding box of the light switch in the scene. The camera pose information includes: the rotation matrix: [[-0.677945, 0.409221, -0.610679], [0.735109, 0.38004, -0.561413], [0.00234, -0.829523, -0.558468]]; the translation vector: [3.092599, 2.044437, 1.437429], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.354, -1.662, 1.012, 0.018, 0.115, 0.103]] B: [[-0.792, -1.485, 1.441, 0.393, -0.105, 0.505]] C: [[-0.528, -1.745, 1.201, 0.1, 0.492, -0.087]] D: [[-0.815, -1.664, 1.36, -0.019, -0.178, -0.353]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_148_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_148_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.747, -2.431, 0.458, 6.984, 5.717, 0.813], [-0.691, 2.68, 0.322, 9.392, 3.093, 0.827]] B: [[0.057, -2.429, 0.573, 7.86, 5.95, 0.072], [-0.235, 2.427, 0.641, 8.832, 2.983, 0.523]] C: [[0.397, -2.595, 0.294, 7.23, 6.005, 0.625], [-0.735, 2.197, 0.57, 9.4, 2.894, 0.932]] D: [[0.26, -2.542, 0.108, 7.4, 6.111, 0.419], [-0.69, 2.286, 0.483, 9.253, 2.675, 0.512]]
Given a RGB image and a depth image, please detect the 3D bounding box of the floor in the scene. The camera pose information includes: the rotation matrix: [[-0.928108, -0.125197, 0.35063], [-0.371823, 0.3599, -0.855699], [-0.019061, -0.924553, -0.380577]]; the translation vector: [5.296664, 4.137775, 1.856988], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.747, -2.431, 0.458, 6.984, 5.717, 0.813], [-0.691, 2.68, 0.322, 9.392, 3.093, 0.827]] B: [[0.057, -2.429, 0.573, 7.86, 5.95, 0.072], [-0.235, 2.427, 0.641, 8.832, 2.983, 0.523]] C: [[0.397, -2.595, 0.294, 7.23, 6.005, 0.625], [-0.735, 2.197, 0.57, 9.4, 2.894, 0.932]] D: [[0.26, -2.542, 0.108, 7.4, 6.111, 0.419], [-0.69, 2.286, 0.483, 9.253, 2.675, 0.512]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_149_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_149_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.374, -0.417, 0.072, 5.927, 4.746, 0.404], [1.639, 0.598, 0.366, 1.118, 4.293, 0.368], [2.9, -1.425, 0.632, 1.428, 0.28, 0.254]] B: [[0.799, -0.748, 0.531, 6.317, 4.867, 0.446], [1.703, 0.912, 0.069, 1.474, 3.826, 0.769], [3.325, -1.637, 0.524, 1.447, 0.08, -0.103]] C: [[0.109, -0.618, 0.303, 6.211, 4.572, 0.089], [2.121, 0.402, 0.274, 1.014, 4.79, 0.298], [2.929, -1.018, 0.279, 1.903, -0.107, 0.311]] D: [[-0.053, -0.73, 0.366, 5.716, 4.946, 0.696], [1.94, 0.414, 0.125, 0.997, 4.139, 0.213], [2.533, -1.383, 0.826, 1.711, 0.446, 0.207]]
Given a RGB image and a depth image, please detect the 3D bounding box of the floor in the scene. The camera pose information includes: the rotation matrix: [[-0.052123, 0.492225, -0.868906], [0.996177, 0.08671, -0.010637], [0.070107, -0.866138, -0.494863]]; the translation vector: [3.27549, 2.071379, 1.287401], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.374, -0.417, 0.072, 5.927, 4.746, 0.404], [1.639, 0.598, 0.366, 1.118, 4.293, 0.368], [2.9, -1.425, 0.632, 1.428, 0.28, 0.254]] B: [[0.799, -0.748, 0.531, 6.317, 4.867, 0.446], [1.703, 0.912, 0.069, 1.474, 3.826, 0.769], [3.325, -1.637, 0.524, 1.447, 0.08, -0.103]] C: [[0.109, -0.618, 0.303, 6.211, 4.572, 0.089], [2.121, 0.402, 0.274, 1.014, 4.79, 0.298], [2.929, -1.018, 0.279, 1.903, -0.107, 0.311]] D: [[-0.053, -0.73, 0.366, 5.716, 4.946, 0.696], [1.94, 0.414, 0.125, 0.997, 4.139, 0.213], [2.533, -1.383, 0.826, 1.711, 0.446, 0.207]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_150_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_150_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.627, -3.376, 0.855, 6.372, 0.045, 1.93], [-4.559, -0.814, 0.815, 0.23, 4.236, 2.315], [2.457, -1.253, 1.135, 0.502, 4.3, 1.849], [2.763, 1.048, 0.711, 0.538, 0.174, 2.307], [2.637, 1.438, 0.737, -0.26, 0.359, 1.655], [2.838, 1.209, 1.15, -0.136, 0.413, 2.018], [2.547, 3.388, 0.7, 0.133, 3.272, 2.033], [1.842, 5.509, 1.228, 1.639, 0.473, 2.533], [1.462, 4.688, 1.401, -0.073, 1.6, 2.078], [3.735, 2.121, 1.265, 0.57, 0.876, 2.223], [3.212, 2.741, 1.782, 1.502, 0.578, -0.004]] B: [[-0.903, -3.755, 0.874, 6.176, 0.003, 1.35], [-4.554, -0.741, 1.026, -0.065, 4.304, 1.597], [2.299, -1.131, 0.865, 0.391, 4.838, 2.495], [2.651, 0.847, 1.18, 0.317, 0.031, 1.522], [1.968, 0.985, 1.174, 0.018, 0.505, 1.538], [2.371, 1.973, 0.767, 0.103, 0.399, 1.514], [2.144, 3.832, 1.306, -0.158, 3.954, 2.582], [1.91, 5.239, 0.926, 1.148, 0.013, 2.526], [1.285, 4.859, 0.706, 0.551, 0.734, 2.356], [3.523, 2.358, 1.085, 0.08, 1.478, 2.236], [3.224, 3.037, 2.38, 1.03, -0.257, 0.188]] C: [[-1.266, -3.485, 0.564, 6.835, 0.324, 1.764], [-3.629, -0.962, 1.016, -0.055, 4.598, 2.313], [2.437, -1.124, 1.463, -0.109, 4.49, 2.527], [2.113, 1.183, 0.667, 0.701, -0.094, 1.699], [2.045, 1.707, 0.812, -0.196, 0.311, 1.762], [2.268, 1.659, 0.591, -0.094, 0.192, 1.734], [2.994, 3.302, 1.563, 0.269, 3.696, 2.084], [1.688, 4.818, 0.728, 1.225, 0.665, 2.09], [0.999, 4.388, 1.202, -0.003, 0.99, 2.125], [3.205, 2.357, 1.438, 0.088, 1.176, 2.548], [3.215, 2.712, 1.754, 0.977, -0.046, 0.843]] D: [[-0.786, -3.408, 0.812, 6.62, 0.23, 1.627], [-4.064, -0.926, 0.97, 0.26, 4.308, 1.916], [2.527, -1.13, 1.126, 0.243, 4.695, 2.21], [2.347, 1.178, 0.964, 0.317, 0.117, 1.88], [2.227, 1.442, 1.014, 0.145, 0.618, 2.004], [2.348, 1.638, 0.879, 0.351, 0.101, 1.748], [2.53, 3.466, 1.165, 0.288, 3.589, 2.389], [1.982, 5.141, 1.204, 1.32, 0.458, 2.309], [1.319, 4.76, 1.151, 0.233, 1.14, 2.044], [3.664, 2.514, 1.17, 0.338, 1.259, 2.387], [3.264, 3.152, 2.173, 1.061, 0.098, 0.435]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.688084, 0.423256, -0.589401], [0.725514, -0.415863, 0.54835], [-0.013017, -0.80493, -0.593227]]; the translation vector: [3.968163, 0.8771, 1.421607], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.627, -3.376, 0.855, 6.372, 0.045, 1.93], [-4.559, -0.814, 0.815, 0.23, 4.236, 2.315], [2.457, -1.253, 1.135, 0.502, 4.3, 1.849], [2.763, 1.048, 0.711, 0.538, 0.174, 2.307], [2.637, 1.438, 0.737, -0.26, 0.359, 1.655], [2.838, 1.209, 1.15, -0.136, 0.413, 2.018], [2.547, 3.388, 0.7, 0.133, 3.272, 2.033], [1.842, 5.509, 1.228, 1.639, 0.473, 2.533], [1.462, 4.688, 1.401, -0.073, 1.6, 2.078], [3.735, 2.121, 1.265, 0.57, 0.876, 2.223], [3.212, 2.741, 1.782, 1.502, 0.578, -0.004]] B: [[-0.903, -3.755, 0.874, 6.176, 0.003, 1.35], [-4.554, -0.741, 1.026, -0.065, 4.304, 1.597], [2.299, -1.131, 0.865, 0.391, 4.838, 2.495], [2.651, 0.847, 1.18, 0.317, 0.031, 1.522], [1.968, 0.985, 1.174, 0.018, 0.505, 1.538], [2.371, 1.973, 0.767, 0.103, 0.399, 1.514], [2.144, 3.832, 1.306, -0.158, 3.954, 2.582], [1.91, 5.239, 0.926, 1.148, 0.013, 2.526], [1.285, 4.859, 0.706, 0.551, 0.734, 2.356], [3.523, 2.358, 1.085, 0.08, 1.478, 2.236], [3.224, 3.037, 2.38, 1.03, -0.257, 0.188]] C: [[-1.266, -3.485, 0.564, 6.835, 0.324, 1.764], [-3.629, -0.962, 1.016, -0.055, 4.598, 2.313], [2.437, -1.124, 1.463, -0.109, 4.49, 2.527], [2.113, 1.183, 0.667, 0.701, -0.094, 1.699], [2.045, 1.707, 0.812, -0.196, 0.311, 1.762], [2.268, 1.659, 0.591, -0.094, 0.192, 1.734], [2.994, 3.302, 1.563, 0.269, 3.696, 2.084], [1.688, 4.818, 0.728, 1.225, 0.665, 2.09], [0.999, 4.388, 1.202, -0.003, 0.99, 2.125], [3.205, 2.357, 1.438, 0.088, 1.176, 2.548], [3.215, 2.712, 1.754, 0.977, -0.046, 0.843]] D: [[-0.786, -3.408, 0.812, 6.62, 0.23, 1.627], [-4.064, -0.926, 0.97, 0.26, 4.308, 1.916], [2.527, -1.13, 1.126, 0.243, 4.695, 2.21], [2.347, 1.178, 0.964, 0.317, 0.117, 1.88], [2.227, 1.442, 1.014, 0.145, 0.618, 2.004], [2.348, 1.638, 0.879, 0.351, 0.101, 1.748], [2.53, 3.466, 1.165, 0.288, 3.589, 2.389], [1.982, 5.141, 1.204, 1.32, 0.458, 2.309], [1.319, 4.76, 1.151, 0.233, 1.14, 2.044], [3.664, 2.514, 1.17, 0.338, 1.259, 2.387], [3.264, 3.152, 2.173, 1.061, 0.098, 0.435]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_151_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_151_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.24, 0.127, 1.561, 0.17, 6.452, 1.322]] B: [[1.808, 0.445, 1.097, -0.163, 6.206, 1.162]] C: [[2.076, -0.046, 1.133, 0.371, 6.595, 0.908]] D: [[2.152, 0.397, 1.838, 0.141, 6.038, 1.758]]
Given a RGB image and a depth image, please detect the 3D bounding box of the whiteboard in the scene. The camera pose information includes: the rotation matrix: [[-0.176261, -0.039155, 0.983564], [-0.983722, -0.028492, -0.177423], [0.03497, -0.998827, -0.033496]]; the translation vector: [3.054739, 2.437738, 1.503838], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[2.24, 0.127, 1.561, 0.17, 6.452, 1.322]] B: [[1.808, 0.445, 1.097, -0.163, 6.206, 1.162]] C: [[2.076, -0.046, 1.133, 0.371, 6.595, 0.908]] D: [[2.152, 0.397, 1.838, 0.141, 6.038, 1.758]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_152_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_152_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.377, 1.75, 0.313, 0.637, 1.084, 1.086], [-0.879, 2.594, 0.422, 0.742, 0.234, 0.85]] B: [[-0.13, 2.575, 0.337, 1.18, 0.166, 1.328], [-0.585, 2.455, 0.693, 0.879, 0.311, 1.309]] C: [[-0.219, 1.756, 0.406, 1.056, 0.511, 0.967], [-0.363, 1.945, 0.501, 1.166, 0.939, 0.804]] D: [[-0.109, 2.202, 0.796, 0.742, 0.65, 0.918], [-0.778, 2.232, 0.83, 0.777, 0.638, 0.953]]
Given a RGB image and a depth image, please detect the 3D bounding box of the sofa chair in the scene. The camera pose information includes: the rotation matrix: [[0.753053, 0.123809, -0.646206], [0.619922, -0.462608, 0.633791], [-0.220471, -0.877875, -0.42512]]; the translation vector: [4.259223, 3.769218, 1.505729], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.377, 1.75, 0.313, 0.637, 1.084, 1.086], [-0.879, 2.594, 0.422, 0.742, 0.234, 0.85]] B: [[-0.13, 2.575, 0.337, 1.18, 0.166, 1.328], [-0.585, 2.455, 0.693, 0.879, 0.311, 1.309]] C: [[-0.219, 1.756, 0.406, 1.056, 0.511, 0.967], [-0.363, 1.945, 0.501, 1.166, 0.939, 0.804]] D: [[-0.109, 2.202, 0.796, 0.742, 0.65, 0.918], [-0.778, 2.232, 0.83, 0.777, 0.638, 0.953]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_153_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_153_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.251, 0.156, -0.128, -0.051, 0.628, 0.239], [0.767, -0.47, 0.609, 0.494, 0.504, 0.166], [-0.094, 1.499, 1.301, 0.409, 0.637, -0.038], [-0.218, 1.599, 2.043, 0.222, -0.051, -0.084], [0.774, 1.201, 1.813, 0.251, -0.38, 0.063]] B: [[-0.408, 0.627, 0.343, 0.188, 0.542, 0.081], [0.501, -0.329, 0.635, 0.154, 0.177, 0.084], [0.343, 1.237, 1.788, 0.265, 0.262, 0.091], [0.216, 1.167, 1.709, 0.275, 0.094, 0.094], [0.467, 1.14, 1.723, 0.259, 0.069, 0.108]] C: [[-0.807, 0.141, 0.815, 0.53, 0.607, 0.51], [0.917, -0.099, 0.427, -0.321, -0.28, 0.334], [0.531, 1.399, 2.196, 0.43, 0.03, 0.076], [0.47, 0.735, 1.914, -0.093, 0.374, 0.55], [-0.032, 1.587, 2.029, 0.611, -0.009, -0.144]] D: [[-0.225, 0.433, 0.214, 0.523, 1.033, -0.125], [0.497, -0.466, 0.903, 0.572, 0.328, -0.033], [0.249, 0.868, 1.316, 0.58, 0.558, -0.337], [0.688, 0.673, 1.442, -0.064, -0.139, -0.391], [0.045, 1.256, 1.359, -0.021, 0.452, 0.403]]
Given a RGB image and a depth image, please detect the 3D bounding box of the towel in the scene. The camera pose information includes: the rotation matrix: [[0.956223, -0.170898, 0.237554], [-0.292595, -0.544035, 0.786393], [-0.005155, -0.821474, -0.570223]]; the translation vector: [1.275326, 2.834272, 1.3185], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.251, 0.156, -0.128, -0.051, 0.628, 0.239], [0.767, -0.47, 0.609, 0.494, 0.504, 0.166], [-0.094, 1.499, 1.301, 0.409, 0.637, -0.038], [-0.218, 1.599, 2.043, 0.222, -0.051, -0.084], [0.774, 1.201, 1.813, 0.251, -0.38, 0.063]] B: [[-0.408, 0.627, 0.343, 0.188, 0.542, 0.081], [0.501, -0.329, 0.635, 0.154, 0.177, 0.084], [0.343, 1.237, 1.788, 0.265, 0.262, 0.091], [0.216, 1.167, 1.709, 0.275, 0.094, 0.094], [0.467, 1.14, 1.723, 0.259, 0.069, 0.108]] C: [[-0.807, 0.141, 0.815, 0.53, 0.607, 0.51], [0.917, -0.099, 0.427, -0.321, -0.28, 0.334], [0.531, 1.399, 2.196, 0.43, 0.03, 0.076], [0.47, 0.735, 1.914, -0.093, 0.374, 0.55], [-0.032, 1.587, 2.029, 0.611, -0.009, -0.144]] D: [[-0.225, 0.433, 0.214, 0.523, 1.033, -0.125], [0.497, -0.466, 0.903, 0.572, 0.328, -0.033], [0.249, 0.868, 1.316, 0.58, 0.558, -0.337], [0.688, 0.673, 1.442, -0.064, -0.139, -0.391], [0.045, 1.256, 1.359, -0.021, 0.452, 0.403]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_154_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_154_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.306, -0.014, 1.979, 4.019, 7.414, 0.307]] B: [[0.103, 0.292, 1.906, 4.176, 7.558, 0.724]] C: [[0.489, 0.437, 1.928, 3.337, 7.327, 0.317]] D: [[0.278, 0.096, 1.983, 3.8, 7.07, 0.334]]
Given a RGB image and a depth image, please detect the 3D bounding box of the ceiling in the scene. The camera pose information includes: the rotation matrix: [[-0.443363, -0.325026, 0.835337], [-0.895367, 0.117125, -0.429651], [0.041809, -0.938424, -0.342946]]; the translation vector: [2.190343, 3.392878, 1.594635], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.306, -0.014, 1.979, 4.019, 7.414, 0.307]] B: [[0.103, 0.292, 1.906, 4.176, 7.558, 0.724]] C: [[0.489, 0.437, 1.928, 3.337, 7.327, 0.317]] D: [[0.278, 0.096, 1.983, 3.8, 7.07, 0.334]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_155_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_155_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.28, 0.304, -0.341, 2.294, 3.044, -0.02], [-1.331, 0.139, -0.157, 1.326, 1.929, 0.397]] B: [[0.062, -0.149, 0.038, 2.484, 2.88, 0.127], [-1.587, -0.328, 0.005, 1.461, 1.909, 0.087]] C: [[0.029, -0.482, -0.368, 2.94, 2.904, 0.128], [-1.213, -0.173, 0.109, 1.128, 1.645, 0.334]] D: [[0.293, -0.453, -0.316, 2.555, 2.944, -0.31], [-1.538, -0.329, -0.099, 1.121, 2.246, -0.19]]
Given a RGB image and a depth image, please detect the 3D bounding box of the floor in the scene. The camera pose information includes: the rotation matrix: [[0.59597, 0.482312, -0.642025], [0.802979, -0.35126, 0.4815], [0.006716, -0.802491, -0.596626]]; the translation vector: [3.449961, 1.112515, 1.412234], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.28, 0.304, -0.341, 2.294, 3.044, -0.02], [-1.331, 0.139, -0.157, 1.326, 1.929, 0.397]] B: [[0.062, -0.149, 0.038, 2.484, 2.88, 0.127], [-1.587, -0.328, 0.005, 1.461, 1.909, 0.087]] C: [[0.029, -0.482, -0.368, 2.94, 2.904, 0.128], [-1.213, -0.173, 0.109, 1.128, 1.645, 0.334]] D: [[0.293, -0.453, -0.316, 2.555, 2.944, -0.31], [-1.538, -0.329, -0.099, 1.121, 2.246, -0.19]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_156_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_156_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.985, 1.36, 0.323, 0.802, 0.423, -0.124], [2.422, 0.684, 0.754, 0.948, 0.198, 0.546], [-0.687, -2.501, -0.196, 0.73, 0.321, 0.703]] B: [[1.365, 1.983, 0.034, 0.504, 0.741, 0.248], [1.92, 1.004, 0.632, 0.401, 0.542, 0.139], [-0.839, -2.927, -0.163, 0.351, 0.752, 0.304]] C: [[1.454, 1.792, 0.377, 0.63, 0.637, 0.263], [2.367, 0.546, 0.29, 0.458, 0.434, 0.427], [-1.072, -2.953, 0.222, 0.398, 0.377, 0.406]] D: [[1.15, 1.795, -0.026, 0.476, 0.371, 0.563], [2.092, 0.112, 0.084, 0.025, 0.591, 0.3], [-1.071, -3.278, 0.072, 0.031, 0.342, 0.689]]
Given a RGB image and a depth image, please detect the 3D bounding box of the seat in the scene. The camera pose information includes: the rotation matrix: [[0.000188, -0.47362, 0.88073], [-0.997828, 0.057931, 0.031365], [-0.065877, -0.878822, -0.47258]]; the translation vector: [4.366519, 5.511691, 1.307889], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.985, 1.36, 0.323, 0.802, 0.423, -0.124], [2.422, 0.684, 0.754, 0.948, 0.198, 0.546], [-0.687, -2.501, -0.196, 0.73, 0.321, 0.703]] B: [[1.365, 1.983, 0.034, 0.504, 0.741, 0.248], [1.92, 1.004, 0.632, 0.401, 0.542, 0.139], [-0.839, -2.927, -0.163, 0.351, 0.752, 0.304]] C: [[1.454, 1.792, 0.377, 0.63, 0.637, 0.263], [2.367, 0.546, 0.29, 0.458, 0.434, 0.427], [-1.072, -2.953, 0.222, 0.398, 0.377, 0.406]] D: [[1.15, 1.795, -0.026, 0.476, 0.371, 0.563], [2.092, 0.112, 0.084, 0.025, 0.591, 0.3], [-1.071, -3.278, 0.072, 0.031, 0.342, 0.689]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_157_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_157_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.531, 1.811, 0.438, 0.96, -0.248, 1.075], [-1.41, -1.002, 0.77, 0.47, 1.246, 1.71]] B: [[-0.951, 1.545, 0.971, 1.428, 0.629, 1.104], [-2.05, -1.043, 0.695, 0.095, 1.11, 1.626]] C: [[-1.029, 1.273, 0.377, 1.0, 0.707, 1.651], [-1.265, -0.353, 1.355, -0.02, 0.917, 2.297]] D: [[-1.312, 1.674, 0.691, 1.103, 0.228, 1.421], [-1.753, -0.603, 0.956, 0.349, 1.091, 2.04]]
Given a RGB image and a depth image, please detect the 3D bounding box of the door in the scene. The camera pose information includes: the rotation matrix: [[0.927869, -0.125596, 0.351119], [-0.372891, -0.32108, 0.870551], [0.003399, -0.938687, -0.344754]]; the translation vector: [5.442723, 4.031985, 1.348893], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.531, 1.811, 0.438, 0.96, -0.248, 1.075], [-1.41, -1.002, 0.77, 0.47, 1.246, 1.71]] B: [[-0.951, 1.545, 0.971, 1.428, 0.629, 1.104], [-2.05, -1.043, 0.695, 0.095, 1.11, 1.626]] C: [[-1.029, 1.273, 0.377, 1.0, 0.707, 1.651], [-1.265, -0.353, 1.355, -0.02, 0.917, 2.297]] D: [[-1.312, 1.674, 0.691, 1.103, 0.228, 1.421], [-1.753, -0.603, 0.956, 0.349, 1.091, 2.04]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_158_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_158_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.1, -0.155, 0.488, 0.884, 0.762, 1.139]] B: [[-1.609, -0.239, 0.938, 0.096, 1.426, 1.078]] C: [[-1.861, -0.273, 0.81, 0.598, 0.82, 0.783]] D: [[-1.644, -0.605, 0.583, 0.402, 1.231, 1.185]]
Given a RGB image and a depth image, please detect the 3D bounding box of the shelf in the scene. The camera pose information includes: the rotation matrix: [[-0.070416, -0.411804, 0.908548], [-0.99671, 0.065705, -0.047468], [-0.040148, -0.908901, -0.415075]]; the translation vector: [2.214543, 1.806687, 1.391502], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-2.1, -0.155, 0.488, 0.884, 0.762, 1.139]] B: [[-1.609, -0.239, 0.938, 0.096, 1.426, 1.078]] C: [[-1.861, -0.273, 0.81, 0.598, 0.82, 0.783]] D: [[-1.644, -0.605, 0.583, 0.402, 1.231, 1.185]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_159_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_159_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.605, -0.075, 2.599, 6.78, 7.188, 0.753]] B: [[-0.136, -0.074, 2.664, 7.091, 7.331, 0.624]] C: [[-0.11, -0.067, 2.645, 6.713, 7.047, 0.627]] D: [[-0.59, -0.552, 3.048, 6.673, 7.52, 0.884]]
Given a RGB image and a depth image, please detect the 3D bounding box of the ceiling in the scene. The camera pose information includes: the rotation matrix: [[-0.955421, 0.119616, -0.269932], [0.295248, 0.388339, -0.872939], [0.000408, -0.91372, -0.406343]]; the translation vector: [2.65583, 2.981598, 1.368648], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.605, -0.075, 2.599, 6.78, 7.188, 0.753]] B: [[-0.136, -0.074, 2.664, 7.091, 7.331, 0.624]] C: [[-0.11, -0.067, 2.645, 6.713, 7.047, 0.627]] D: [[-0.59, -0.552, 3.048, 6.673, 7.52, 0.884]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_160_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_160_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.773, 0.999, 2.176, 3.762, 2.16, 0.713]] B: [[1.402, 0.542, 2.42, 3.544, 2.145, 0.268]] C: [[0.962, 0.894, 1.956, 3.984, 2.23, 0.213]] D: [[1.508, 0.544, 2.14, 3.898, 2.009, 0.701]]
Given a RGB image and a depth image, please detect the 3D bounding box of the ceiling in the scene. The camera pose information includes: the rotation matrix: [[-0.454685, 0.144673, -0.878824], [0.890085, 0.109034, -0.442562], [0.031795, -0.983454, -0.178347]]; the translation vector: [3.311996, 2.119304, 1.59409], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.773, 0.999, 2.176, 3.762, 2.16, 0.713]] B: [[1.402, 0.542, 2.42, 3.544, 2.145, 0.268]] C: [[0.962, 0.894, 1.956, 3.984, 2.23, 0.213]] D: [[1.508, 0.544, 2.14, 3.898, 2.009, 0.701]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_161_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_161_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.445, -1.591, 0.401, 1.208, 0.362, 0.709], [0.85, 1.846, 0.287, 0.495, 1.135, -0.015]] B: [[1.318, -1.383, 0.256, 0.782, 0.724, 0.542], [1.339, 2.155, 0.239, 0.765, 0.899, 0.445]] C: [[1.731, -1.727, 0.665, 0.715, 0.694, 0.718], [0.941, 2.531, -0.018, 1.235, 0.51, 0.14]] D: [[1.454, -1.414, -0.024, 0.443, 0.46, 0.088], [0.989, 2.555, 0.477, 1.003, 1.282, 0.286]]
Given a RGB image and a depth image, please detect the 3D bounding box of the coffee table in the scene. The camera pose information includes: the rotation matrix: [[0.990268, -0.101591, 0.095124], [-0.135934, -0.559426, 0.817658], [-0.029851, -0.822631, -0.567792]]; the translation vector: [6.679901, 2.488796, 1.402653], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.445, -1.591, 0.401, 1.208, 0.362, 0.709], [0.85, 1.846, 0.287, 0.495, 1.135, -0.015]] B: [[1.318, -1.383, 0.256, 0.782, 0.724, 0.542], [1.339, 2.155, 0.239, 0.765, 0.899, 0.445]] C: [[1.731, -1.727, 0.665, 0.715, 0.694, 0.718], [0.941, 2.531, -0.018, 1.235, 0.51, 0.14]] D: [[1.454, -1.414, -0.024, 0.443, 0.46, 0.088], [0.989, 2.555, 0.477, 1.003, 1.282, 0.286]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_162_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_162_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.849, -1.336, 0.075, 0.117, 0.119, 0.051]] B: [[1.779, -1.476, 0.442, 0.485, 0.615, 0.395]] C: [[1.904, -1.448, 0.152, 0.474, 0.108, -0.174]] D: [[1.427, -1.203, 0.391, 0.059, -0.193, -0.208]]
Given a RGB image and a depth image, please detect the 3D bounding box of the object in the scene. The camera pose information includes: the rotation matrix: [[0.246516, -0.470365, 0.847341], [-0.959136, 0.006886, 0.282862], [-0.138884, -0.882445, -0.449446]]; the translation vector: [3.043058, 2.955299, 1.551102], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.849, -1.336, 0.075, 0.117, 0.119, 0.051]] B: [[1.779, -1.476, 0.442, 0.485, 0.615, 0.395]] C: [[1.904, -1.448, 0.152, 0.474, 0.108, -0.174]] D: [[1.427, -1.203, 0.391, 0.059, -0.193, -0.208]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_163_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_163_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.487, 1.645, 0.382, 0.302, 0.482, 0.482], [0.998, 1.485, 0.258, 0.64, 0.279, 0.771], [0.516, 1.799, 0.05, 0.639, 0.719, 0.616], [0.027, 2.307, 0.334, 0.459, 0.957, 1.087], [-0.766, 2.114, 0.879, 0.637, 0.926, 1.186], [-1.637, 1.716, 0.195, 0.889, 0.178, 0.887], [-1.878, 1.498, 0.042, 1.014, 0.211, 0.465], [-2.168, 2.812, 0.748, 0.089, 0.133, 0.111], [-2.511, -0.128, 0.278, 0.262, 0.627, 1.122], [-3.252, -1.403, 0.351, 0.543, 0.875, 0.964], [-2.67, -1.518, 0.047, 0.142, 0.368, 0.87], [-0.679, -1.008, 0.86, 0.74, 0.76, 1.005], [-0.054, -1.776, 0.013, 0.602, 0.383, 0.483], [0.442, -1.702, 0.129, 0.294, 0.491, 1.264], [-0.906, -1.527, 0.588, 0.773, 1.129, 1.323], [1.797, -0.711, 0.306, 0.186, 0.995, 1.019], [1.694, -1.236, 0.46, 0.778, 1.151, 1.284], [1.24, -1.901, 0.667, 0.364, 1.023, 0.918], [2.398, -1.858, 0.981, 0.284, 0.726, 0.83], [3.224, -1.673, 0.285, 0.245, 0.491, 0.975], [1.768, 2.317, 0.9, 0.325, 1.027, 1.062], [1.496, 2.661, 0.93, -0.007, 0.819, 0.169]] B: [[1.146, 0.948, 0.122, 0.95, 1.005, 0.549], [0.748, 0.973, 0.155, 0.6, 0.484, 0.381], [0.549, 2.17, 0.091, 0.666, 0.717, 0.866], [0.554, 2.811, 0.815, 0.733, 0.125, 0.7], [-0.925, 2.187, 0.558, 0.622, 0.213, 0.874], [-1.744, 1.277, 0.001, 0.646, 0.973, 0.704], [-1.809, 2.353, 0.808, 0.048, 0.797, 0.7], [-1.256, 2.641, 1.036, 0.522, 0.609, 0.158], [-1.879, -0.087, 0.596, 0.81, 0.571, 0.463], [-3.345, -0.961, 0.298, 0.354, 0.59, 1.207], [-2.802, -1.895, 0.135, 0.976, 1.183, 0.764], [-0.847, -1.618, 0.508, 0.783, 0.348, 1.292], [-0.511, -1.056, 0.376, 0.73, 0.392, 1.159], [-0.024, -2.057, 0.759, 0.532, 0.455, 0.817], [-0.251, -2.214, 0.173, 1.127, 0.862, 0.708], [2.174, -0.228, 0.822, 0.364, 0.554, 0.827], [1.928, -1.877, 0.198, 0.653, 1.131, 1.053], [1.218, -2.319, 0.663, 0.163, 0.153, 0.793], [2.951, -1.156, 0.405, 1.011, 0.624, 0.772], [3.153, -1.986, 0.421, 0.263, 0.33, 0.7], [1.367, 2.28, 0.547, 1.058, 0.935, 1.287], [2.006, 2.966, 0.782, 0.332, 0.619, 0.04]] C: [[1.346, 1.054, 0.767, 0.951, 0.758, 0.769], [0.659, 1.706, 0.684, 0.913, 0.914, 1.319], [0.805, 2.288, 0.288, 0.155, 0.839, 0.635], [0.287, 2.236, 0.545, 0.587, 0.976, 0.783], [-1.118, 2.319, 0.772, 1.192, 0.851, 0.415], [-1.552, 1.463, 0.231, 0.636, 0.79, 0.457], [-1.992, 2.15, 0.851, 0.919, 1.11, 0.624], [-1.923, 2.253, 1.26, 0.407, 0.257, 0.58], [-2.064, -0.023, 0.196, 0.32, 0.999, 0.859], [-3.224, -1.369, 0.324, 1.046, 0.849, 0.941], [-2.953, -2.153, 0.953, 0.315, 0.426, 0.39], [-0.29, -1.189, 0.464, 0.368, 1.039, 1.28], [-0.098, -2.0, 0.391, 0.817, 0.212, 1.036], [0.365, -1.822, 0.164, 0.214, 0.365, 0.378], [-0.847, -2.191, 0.875, 0.968, 0.479, 0.553], [2.332, -0.438, 0.431, 0.138, 0.956, 1.041], [1.345, -2.004, 0.538, 0.439, 0.287, 0.73], [1.393, -1.64, 0.88, 0.322, 0.297, 1.16], [3.052, -1.259, 0.761, 0.943, 0.828, 0.5], [2.735, -2.476, 0.875, 0.335, 1.087, 0.495], [1.336, 2.088, 0.504, 0.673, 1.053, 0.469], [1.386, 2.116, 0.605, 0.191, 0.61, 0.101]] D: [[1.518, 1.271, 0.394, 0.605, 0.594, 0.849], [0.943, 1.353, 0.378, 0.619, 0.666, 0.828], [0.701, 1.955, 0.404, 0.648, 0.696, 0.84], [0.523, 2.479, 0.454, 0.541, 0.563, 0.792], [-1.051, 2.117, 0.448, 0.79, 0.709, 0.804], [-1.341, 1.248, 0.462, 0.57, 0.622, 0.853], [-1.574, 1.994, 0.519, 0.538, 0.675, 0.779], [-1.737, 2.403, 0.858, 0.16, 0.317, 0.168], [-2.078, -0.466, 0.495, 0.568, 0.586, 0.801], [-2.925, -1.082, 0.538, 0.66, 0.66, 0.803], [-3.037, -1.752, 0.519, 0.574, 0.705, 0.845], [-0.539, -1.191, 0.375, 0.64, 0.637, 0.843], [-0.068, -1.536, 0.384, 0.646, 0.641, 0.825], [-0.052, -2.09, 0.408, 0.661, 0.773, 0.824], [-0.669, -1.919, 0.395, 0.676, 0.647, 0.832], [2.151, -0.689, 0.438, 0.636, 0.62, 0.802], [1.695, -1.528, 0.421, 0.589, 0.733, 0.82], [1.703, -2.028, 0.457, 0.561, 0.65, 0.798], [2.65, -1.483, 0.534, 0.701, 0.712, 0.852], [2.844, -2.087, 0.588, 0.548, 0.714, 0.804], [1.775, 1.985, 0.459, 0.664, 0.67, 0.811], [1.768, 2.603, 0.602, 0.329, 0.514, 0.537]]
Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[0.424269, -0.366439, 0.828081], [-0.894198, -0.025281, 0.446957], [-0.142848, -0.930098, -0.338395]]; the translation vector: [2.638367, 6.760901, 1.41712], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.487, 1.645, 0.382, 0.302, 0.482, 0.482], [0.998, 1.485, 0.258, 0.64, 0.279, 0.771], [0.516, 1.799, 0.05, 0.639, 0.719, 0.616], [0.027, 2.307, 0.334, 0.459, 0.957, 1.087], [-0.766, 2.114, 0.879, 0.637, 0.926, 1.186], [-1.637, 1.716, 0.195, 0.889, 0.178, 0.887], [-1.878, 1.498, 0.042, 1.014, 0.211, 0.465], [-2.168, 2.812, 0.748, 0.089, 0.133, 0.111], [-2.511, -0.128, 0.278, 0.262, 0.627, 1.122], [-3.252, -1.403, 0.351, 0.543, 0.875, 0.964], [-2.67, -1.518, 0.047, 0.142, 0.368, 0.87], [-0.679, -1.008, 0.86, 0.74, 0.76, 1.005], [-0.054, -1.776, 0.013, 0.602, 0.383, 0.483], [0.442, -1.702, 0.129, 0.294, 0.491, 1.264], [-0.906, -1.527, 0.588, 0.773, 1.129, 1.323], [1.797, -0.711, 0.306, 0.186, 0.995, 1.019], [1.694, -1.236, 0.46, 0.778, 1.151, 1.284], [1.24, -1.901, 0.667, 0.364, 1.023, 0.918], [2.398, -1.858, 0.981, 0.284, 0.726, 0.83], [3.224, -1.673, 0.285, 0.245, 0.491, 0.975], [1.768, 2.317, 0.9, 0.325, 1.027, 1.062], [1.496, 2.661, 0.93, -0.007, 0.819, 0.169]] B: [[1.146, 0.948, 0.122, 0.95, 1.005, 0.549], [0.748, 0.973, 0.155, 0.6, 0.484, 0.381], [0.549, 2.17, 0.091, 0.666, 0.717, 0.866], [0.554, 2.811, 0.815, 0.733, 0.125, 0.7], [-0.925, 2.187, 0.558, 0.622, 0.213, 0.874], [-1.744, 1.277, 0.001, 0.646, 0.973, 0.704], [-1.809, 2.353, 0.808, 0.048, 0.797, 0.7], [-1.256, 2.641, 1.036, 0.522, 0.609, 0.158], [-1.879, -0.087, 0.596, 0.81, 0.571, 0.463], [-3.345, -0.961, 0.298, 0.354, 0.59, 1.207], [-2.802, -1.895, 0.135, 0.976, 1.183, 0.764], [-0.847, -1.618, 0.508, 0.783, 0.348, 1.292], [-0.511, -1.056, 0.376, 0.73, 0.392, 1.159], [-0.024, -2.057, 0.759, 0.532, 0.455, 0.817], [-0.251, -2.214, 0.173, 1.127, 0.862, 0.708], [2.174, -0.228, 0.822, 0.364, 0.554, 0.827], [1.928, -1.877, 0.198, 0.653, 1.131, 1.053], [1.218, -2.319, 0.663, 0.163, 0.153, 0.793], [2.951, -1.156, 0.405, 1.011, 0.624, 0.772], [3.153, -1.986, 0.421, 0.263, 0.33, 0.7], [1.367, 2.28, 0.547, 1.058, 0.935, 1.287], [2.006, 2.966, 0.782, 0.332, 0.619, 0.04]] C: [[1.346, 1.054, 0.767, 0.951, 0.758, 0.769], [0.659, 1.706, 0.684, 0.913, 0.914, 1.319], [0.805, 2.288, 0.288, 0.155, 0.839, 0.635], [0.287, 2.236, 0.545, 0.587, 0.976, 0.783], [-1.118, 2.319, 0.772, 1.192, 0.851, 0.415], [-1.552, 1.463, 0.231, 0.636, 0.79, 0.457], [-1.992, 2.15, 0.851, 0.919, 1.11, 0.624], [-1.923, 2.253, 1.26, 0.407, 0.257, 0.58], [-2.064, -0.023, 0.196, 0.32, 0.999, 0.859], [-3.224, -1.369, 0.324, 1.046, 0.849, 0.941], [-2.953, -2.153, 0.953, 0.315, 0.426, 0.39], [-0.29, -1.189, 0.464, 0.368, 1.039, 1.28], [-0.098, -2.0, 0.391, 0.817, 0.212, 1.036], [0.365, -1.822, 0.164, 0.214, 0.365, 0.378], [-0.847, -2.191, 0.875, 0.968, 0.479, 0.553], [2.332, -0.438, 0.431, 0.138, 0.956, 1.041], [1.345, -2.004, 0.538, 0.439, 0.287, 0.73], [1.393, -1.64, 0.88, 0.322, 0.297, 1.16], [3.052, -1.259, 0.761, 0.943, 0.828, 0.5], [2.735, -2.476, 0.875, 0.335, 1.087, 0.495], [1.336, 2.088, 0.504, 0.673, 1.053, 0.469], [1.386, 2.116, 0.605, 0.191, 0.61, 0.101]] D: [[1.518, 1.271, 0.394, 0.605, 0.594, 0.849], [0.943, 1.353, 0.378, 0.619, 0.666, 0.828], [0.701, 1.955, 0.404, 0.648, 0.696, 0.84], [0.523, 2.479, 0.454, 0.541, 0.563, 0.792], [-1.051, 2.117, 0.448, 0.79, 0.709, 0.804], [-1.341, 1.248, 0.462, 0.57, 0.622, 0.853], [-1.574, 1.994, 0.519, 0.538, 0.675, 0.779], [-1.737, 2.403, 0.858, 0.16, 0.317, 0.168], [-2.078, -0.466, 0.495, 0.568, 0.586, 0.801], [-2.925, -1.082, 0.538, 0.66, 0.66, 0.803], [-3.037, -1.752, 0.519, 0.574, 0.705, 0.845], [-0.539, -1.191, 0.375, 0.64, 0.637, 0.843], [-0.068, -1.536, 0.384, 0.646, 0.641, 0.825], [-0.052, -2.09, 0.408, 0.661, 0.773, 0.824], [-0.669, -1.919, 0.395, 0.676, 0.647, 0.832], [2.151, -0.689, 0.438, 0.636, 0.62, 0.802], [1.695, -1.528, 0.421, 0.589, 0.733, 0.82], [1.703, -2.028, 0.457, 0.561, 0.65, 0.798], [2.65, -1.483, 0.534, 0.701, 0.712, 0.852], [2.844, -2.087, 0.588, 0.548, 0.714, 0.804], [1.775, 1.985, 0.459, 0.664, 0.67, 0.811], [1.768, 2.603, 0.602, 0.329, 0.514, 0.537]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_164_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_164_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.682, 0.363, 0.619, 1.02, 0.762, 0.226], [0.295, -1.101, 1.206, 0.33, 0.677, 0.052], [-2.902, 0.765, -0.248, 0.755, 0.487, 0.427]] B: [[2.599, 0.763, 0.355, 0.291, 0.253, 0.563], [0.364, -0.942, 0.366, 0.823, 0.285, 0.293], [-3.251, -0.039, 0.534, 0.204, 0.315, 0.125]] C: [[2.754, 0.716, 0.728, 0.739, 0.536, 0.095], [-0.308, -0.319, 1.147, 0.102, 0.805, 0.177], [-3.102, -0.022, 0.312, 0.658, 0.474, 0.358]] D: [[2.461, 0.569, 0.328, 0.546, 0.491, 0.37], [-0.048, -0.818, 0.757, 0.462, 0.439, 0.351], [-2.848, 0.285, 0.131, 0.472, 0.5, 0.37]]
Given a RGB image and a depth image, please detect the 3D bounding box of the box in the scene. The camera pose information includes: the rotation matrix: [[0.764638, 0.028658, -0.643823], [0.64431, -0.055554, 0.762744], [-0.013909, -0.998044, -0.060944]]; the translation vector: [3.061982, 3.98913, 1.495508], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[2.682, 0.363, 0.619, 1.02, 0.762, 0.226], [0.295, -1.101, 1.206, 0.33, 0.677, 0.052], [-2.902, 0.765, -0.248, 0.755, 0.487, 0.427]] B: [[2.599, 0.763, 0.355, 0.291, 0.253, 0.563], [0.364, -0.942, 0.366, 0.823, 0.285, 0.293], [-3.251, -0.039, 0.534, 0.204, 0.315, 0.125]] C: [[2.754, 0.716, 0.728, 0.739, 0.536, 0.095], [-0.308, -0.319, 1.147, 0.102, 0.805, 0.177], [-3.102, -0.022, 0.312, 0.658, 0.474, 0.358]] D: [[2.461, 0.569, 0.328, 0.546, 0.491, 0.37], [-0.048, -0.818, 0.757, 0.462, 0.439, 0.351], [-2.848, 0.285, 0.131, 0.472, 0.5, 0.37]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_165_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_165_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.116, -0.769, 0.665, 0.588, 1.197, 1.025], [-0.796, -1.178, 0.171, 0.576, 0.604, 0.431], [-0.822, 1.221, 0.066, 0.696, 1.356, 0.542], [0.425, 0.671, 0.344, 0.824, 1.179, 0.866]] B: [[0.608, -0.936, 0.413, 0.854, 0.8, 0.77], [-0.425, -0.856, 0.339, 0.897, 0.767, 0.762], [-0.451, 1.126, 0.358, 0.838, 0.91, 0.764], [0.774, 1.047, 0.416, 0.815, 0.841, 0.775]] C: [[0.288, -1.283, 0.655, 0.817, 0.674, 0.566], [-0.233, -0.57, 0.023, 0.569, 0.942, 1.169], [-0.037, 0.77, 0.308, 0.824, 1.383, 0.685], [0.662, 1.515, 0.896, 0.594, 0.416, 0.9]] D: [[1.018, -1.113, 0.375, 0.665, 0.803, 1.039], [-0.701, -1.19, 0.042, 0.611, 0.648, 0.566], [-0.236, 1.15, 0.63, 1.12, 1.165, 0.969], [0.285, 0.606, 0.443, 1.268, 0.881, 0.591]]
Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.711391, -0.463973, 0.527875], [-0.700286, 0.531398, -0.476672], [-0.059349, -0.708763, -0.702945]]; the translation vector: [2.53321, 4.394931, 1.530427], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.116, -0.769, 0.665, 0.588, 1.197, 1.025], [-0.796, -1.178, 0.171, 0.576, 0.604, 0.431], [-0.822, 1.221, 0.066, 0.696, 1.356, 0.542], [0.425, 0.671, 0.344, 0.824, 1.179, 0.866]] B: [[0.608, -0.936, 0.413, 0.854, 0.8, 0.77], [-0.425, -0.856, 0.339, 0.897, 0.767, 0.762], [-0.451, 1.126, 0.358, 0.838, 0.91, 0.764], [0.774, 1.047, 0.416, 0.815, 0.841, 0.775]] C: [[0.288, -1.283, 0.655, 0.817, 0.674, 0.566], [-0.233, -0.57, 0.023, 0.569, 0.942, 1.169], [-0.037, 0.77, 0.308, 0.824, 1.383, 0.685], [0.662, 1.515, 0.896, 0.594, 0.416, 0.9]] D: [[1.018, -1.113, 0.375, 0.665, 0.803, 1.039], [-0.701, -1.19, 0.042, 0.611, 0.648, 0.566], [-0.236, 1.15, 0.63, 1.12, 1.165, 0.969], [0.285, 0.606, 0.443, 1.268, 0.881, 0.591]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_166_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_166_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.097, 1.124, 0.669, 0.502, 0.516, 0.549], [-0.719, 0.622, 0.51, 0.696, 0.696, 1.008], [0.747, 0.329, 0.449, 0.568, 0.565, 0.934], [0.72, 0.839, 0.522, 0.626, 0.707, 0.997], [-0.373, -0.636, 0.467, 0.582, 0.551, 0.906]] B: [[0.297, 0.852, 0.7, 0.103, 0.44, 0.966], [-0.93, 0.904, 0.062, 0.986, 0.828, 0.767], [0.468, 0.69, 0.657, 0.758, 0.619, 1.108], [0.682, 0.702, 0.346, 0.75, 0.569, 0.847], [-0.423, -0.68, 0.291, 0.082, 0.385, 1.192]] C: [[0.512, 0.853, 0.312, 0.021, 0.921, 0.339], [-0.518, 0.57, 0.844, 1.067, 0.275, 1.347], [0.721, 0.423, 0.574, 0.387, 0.991, 1.286], [0.648, 0.46, 0.149, 0.657, 0.835, 0.53], [-0.541, -0.731, 0.203, 0.127, 0.654, 0.996]] D: [[0.168, 0.81, 1.159, 0.247, 0.182, 0.73], [-0.91, 0.423, 0.9, 0.946, 0.519, 0.547], [1.221, 0.571, 0.284, 0.571, 0.987, 1.376], [1.146, 0.534, 0.507, 0.778, 0.702, 1.372], [-0.13, -0.402, 0.492, 0.884, 0.774, 1.331]]
Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.236277, -0.452541, 0.859872], [-0.970097, 0.160455, -0.182119], [-0.055554, -0.877189, -0.47692]]; the translation vector: [1.575898, 1.961144, 1.314442], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.097, 1.124, 0.669, 0.502, 0.516, 0.549], [-0.719, 0.622, 0.51, 0.696, 0.696, 1.008], [0.747, 0.329, 0.449, 0.568, 0.565, 0.934], [0.72, 0.839, 0.522, 0.626, 0.707, 0.997], [-0.373, -0.636, 0.467, 0.582, 0.551, 0.906]] B: [[0.297, 0.852, 0.7, 0.103, 0.44, 0.966], [-0.93, 0.904, 0.062, 0.986, 0.828, 0.767], [0.468, 0.69, 0.657, 0.758, 0.619, 1.108], [0.682, 0.702, 0.346, 0.75, 0.569, 0.847], [-0.423, -0.68, 0.291, 0.082, 0.385, 1.192]] C: [[0.512, 0.853, 0.312, 0.021, 0.921, 0.339], [-0.518, 0.57, 0.844, 1.067, 0.275, 1.347], [0.721, 0.423, 0.574, 0.387, 0.991, 1.286], [0.648, 0.46, 0.149, 0.657, 0.835, 0.53], [-0.541, -0.731, 0.203, 0.127, 0.654, 0.996]] D: [[0.168, 0.81, 1.159, 0.247, 0.182, 0.73], [-0.91, 0.423, 0.9, 0.946, 0.519, 0.547], [1.221, 0.571, 0.284, 0.571, 0.987, 1.376], [1.146, 0.534, 0.507, 0.778, 0.702, 1.372], [-0.13, -0.402, 0.492, 0.884, 0.774, 1.331]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_167_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_167_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.094, 0.511, 1.124, 0.123, 2.188, 0.539]] B: [[2.081, 0.516, 0.947, 0.355, 2.545, 0.592]] C: [[1.732, 0.343, 0.947, 0.511, 2.586, 0.308]] D: [[1.989, 0.949, 0.649, -0.276, 2.128, 0.539]]
Given a RGB image and a depth image, please detect the 3D bounding box of the whiteboard in the scene. The camera pose information includes: the rotation matrix: [[-0.997074, 0.061747, -0.045056], [0.074474, 0.651998, -0.754554], [-0.017215, -0.755702, -0.654689]]; the translation vector: [1.815792, 5.369752, 1.288561], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[2.094, 0.511, 1.124, 0.123, 2.188, 0.539]] B: [[2.081, 0.516, 0.947, 0.355, 2.545, 0.592]] C: [[1.732, 0.343, 0.947, 0.511, 2.586, 0.308]] D: [[1.989, 0.949, 0.649, -0.276, 2.128, 0.539]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_168_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_168_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.228, -1.39, 0.131, 0.85, 0.551, 0.683]] B: [[-1.305, -1.508, 0.232, 0.822, 0.566, 0.435]] C: [[-0.824, -1.786, 0.652, 1.27, 0.727, -0.053]] D: [[-0.844, -1.175, 0.453, 0.328, 0.627, 0.359]]
Given a RGB image and a depth image, please detect the 3D bounding box of the piano bench in the scene. The camera pose information includes: the rotation matrix: [[-0.804945, -0.278842, 0.523748], [-0.593014, 0.407765, -0.694307], [-0.019964, -0.869468, -0.493585]]; the translation vector: [4.871809, 2.494869, 1.402737], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.228, -1.39, 0.131, 0.85, 0.551, 0.683]] B: [[-1.305, -1.508, 0.232, 0.822, 0.566, 0.435]] C: [[-0.824, -1.786, 0.652, 1.27, 0.727, -0.053]] D: [[-0.844, -1.175, 0.453, 0.328, 0.627, 0.359]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_169_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_169_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.141, 1.242, 1.15, 2.629, 0.737, 2.324], [-1.855, -0.469, 1.171, 0.539, 3.779, 2.772], [0.841, 0.114, 0.787, 0.691, 3.588, 2.223], [0.571, -1.772, 1.52, 1.679, 0.887, 2.594]] B: [[-0.097, 1.504, 1.106, 3.029, 0.358, 2.218], [-1.545, 0.258, 1.211, 0.132, 3.756, 2.16], [0.905, 0.283, 1.397, -0.093, 3.002, 2.004], [0.394, -1.669, 1.139, 2.247, 0.169, 2.208]] C: [[-0.253, 1.653, 1.522, 3.078, 0.478, 2.791], [-1.503, -0.37, 1.376, 0.691, 4.127, 2.703], [1.422, -0.022, 0.986, 0.339, 3.887, 2.497], [-0.134, -1.344, 0.891, 2.344, 0.714, 2.451]] D: [[-0.058, 1.533, 1.269, 2.876, 0.624, 2.668], [-1.389, 0.007, 1.251, 0.231, 3.638, 2.637], [1.275, 0.042, 1.086, 0.289, 3.412, 2.272], [0.358, -1.537, 1.122, 1.906, 0.425, 2.129]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.032646, 0.194727, -0.980314], [0.998594, -0.034636, -0.040135], [-0.04177, -0.980246, -0.193322]]; the translation vector: [3.506056, 2.493951, 1.706783], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.141, 1.242, 1.15, 2.629, 0.737, 2.324], [-1.855, -0.469, 1.171, 0.539, 3.779, 2.772], [0.841, 0.114, 0.787, 0.691, 3.588, 2.223], [0.571, -1.772, 1.52, 1.679, 0.887, 2.594]] B: [[-0.097, 1.504, 1.106, 3.029, 0.358, 2.218], [-1.545, 0.258, 1.211, 0.132, 3.756, 2.16], [0.905, 0.283, 1.397, -0.093, 3.002, 2.004], [0.394, -1.669, 1.139, 2.247, 0.169, 2.208]] C: [[-0.253, 1.653, 1.522, 3.078, 0.478, 2.791], [-1.503, -0.37, 1.376, 0.691, 4.127, 2.703], [1.422, -0.022, 0.986, 0.339, 3.887, 2.497], [-0.134, -1.344, 0.891, 2.344, 0.714, 2.451]] D: [[-0.058, 1.533, 1.269, 2.876, 0.624, 2.668], [-1.389, 0.007, 1.251, 0.231, 3.638, 2.637], [1.275, 0.042, 1.086, 0.289, 3.412, 2.272], [0.358, -1.537, 1.122, 1.906, 0.425, 2.129]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_170_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_170_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.22, -0.005, 0.817, 1.09, 2.894, 0.662], [-2.657, -0.552, 1.11, 0.97, 1.155, 0.566]] B: [[-1.955, 0.127, 0.536, 1.492, 2.79, 1.348], [-2.155, 0.305, 0.66, 0.159, 1.455, 0.072]] C: [[-1.433, 0.186, 1.02, 1.626, 2.332, 1.534], [-2.448, -0.356, 0.853, 0.017, 1.445, 0.618]] D: [[-1.798, 0.428, 0.571, 1.201, 2.441, 1.114], [-2.518, -0.083, 1.081, 0.488, 1.535, 0.157]]
Given a RGB image and a depth image, please detect the 3D bounding box of the couch in the scene. The camera pose information includes: the rotation matrix: [[-0.205964, -0.505778, 0.837716], [-0.978495, 0.11627, -0.170378], [-0.011228, -0.854792, -0.518849]]; the translation vector: [2.901534, 4.292832, 1.280844], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-2.22, -0.005, 0.817, 1.09, 2.894, 0.662], [-2.657, -0.552, 1.11, 0.97, 1.155, 0.566]] B: [[-1.955, 0.127, 0.536, 1.492, 2.79, 1.348], [-2.155, 0.305, 0.66, 0.159, 1.455, 0.072]] C: [[-1.433, 0.186, 1.02, 1.626, 2.332, 1.534], [-2.448, -0.356, 0.853, 0.017, 1.445, 0.618]] D: [[-1.798, 0.428, 0.571, 1.201, 2.441, 1.114], [-2.518, -0.083, 1.081, 0.488, 1.535, 0.157]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_171_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_171_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.442, -1.133, 0.562, 0.636, 0.657, 0.49], [-0.931, -0.023, 0.592, 0.548, 0.635, 0.449], [1.185, -0.67, 0.523, 0.55, 0.618, 0.447], [-0.778, 1.905, 0.84, 0.606, 0.538, 0.514], [-0.723, -1.153, 0.514, 0.657, 0.632, 0.473], [-1.434, -0.489, 0.591, 0.567, 0.545, 0.458], [-1.479, -1.704, 0.547, 0.555, 0.643, 0.506], [-1.06, 0.579, 0.646, 0.554, 0.57, 0.426], [1.728, -0.095, 0.592, 0.547, 0.596, 0.473], [-1.358, 1.889, 0.774, 0.643, 0.662, 0.446], [2.187, 1.992, 0.739, 0.592, 0.503, 0.463], [-0.349, 1.313, 0.568, 0.481, 0.31, 0.827], [0.659, 1.035, 0.643, 0.561, 0.458, 0.449], [1.351, 1.116, 0.663, 0.567, 0.545, 0.469], [1.67, 0.521, 0.73, 0.179, 0.508, 0.285], [0.482, -0.974, 0.492, 0.592, 0.586, 0.475]] B: [[-1.049, -1.529, 1.034, 0.201, 0.822, 0.539], [-0.9, 0.339, 0.327, 0.273, 0.766, 0.553], [0.737, -1.05, 0.211, 0.082, 0.504, 0.933], [-1.047, 2.226, 0.838, 0.996, 0.859, 0.972], [-0.719, -0.678, 0.784, 0.49, 0.145, 0.261], [-1.882, -0.392, 0.818, 0.955, 0.143, 0.713], [-1.551, -2.013, 0.366, 0.53, 0.75, 0.368], [-1.315, 0.463, 0.891, 0.81, 0.604, 0.638], [2.147, -0.334, 0.803, 0.499, 0.844, 0.692], [-1.677, 2.042, 0.864, 0.402, 1.157, 0.639], [1.976, 2.077, 0.904, 0.918, 0.711, 0.254], [-0.187, 1.603, 0.781, 0.267, -0.088, 1.027], [0.26, 0.795, 0.514, 0.847, -0.04, 0.297], [1.756, 1.456, 0.644, 0.597, 0.817, 0.47], [1.242, 0.068, 0.373, 0.448, 0.149, 0.381], [0.319, -0.553, 0.655, 0.691, 0.359, 0.589]] C: [[-0.988, -1.282, 0.732, 0.336, 0.483, 0.927], [-0.442, -0.073, 0.808, 0.229, 0.772, 0.639], [1.548, -1.036, 0.108, 0.525, 0.245, 0.035], [-1.266, 1.685, 1.335, 0.956, 0.747, 0.267], [-1.079, -1.607, 1.01, 0.83, 1.062, 0.521], [-1.264, -0.925, 0.343, 1.047, 0.715, 0.269], [-1.458, -1.958, 0.337, 0.66, 0.161, 0.546], [-0.733, 0.312, 0.474, 0.521, 0.178, -0.061], [2.105, 0.263, 0.727, 0.39, 0.976, 0.108], [-1.707, 1.787, 0.496, 0.472, 1.062, 0.821], [2.45, 1.544, 0.321, 1.018, 0.15, 0.075], [-0.837, 1.59, 0.268, 0.538, 0.245, 0.497], [0.297, 1.19, 0.423, 0.185, 0.686, 0.323], [0.857, 1.058, 0.937, 0.887, 0.209, 0.519], [1.802, 0.184, 0.797, 0.22, 0.094, 0.637], [0.094, -0.987, 0.725, 0.553, 1.059, 0.036]] D: [[-1.227, -0.819, 0.642, 0.301, 0.736, 0.894], [-1.335, 0.35, 0.132, 0.881, 0.202, 0.441], [1.374, -0.345, 0.698, 0.363, 1.089, 0.667], [-0.963, 1.843, 0.91, 0.493, 0.498, 0.35], [-1.186, -1.506, 0.169, 0.581, 0.638, 0.951], [-1.772, -0.025, 0.967, 0.473, 0.884, -0.032], [-1.614, -1.94, 0.374, 0.725, 0.441, 0.512], [-1.408, 0.285, 1.05, 0.486, 0.297, 0.835], [2.021, -0.535, 0.654, 0.219, 0.759, 0.901], [-1.57, 2.203, 0.527, 0.16, 0.291, 0.718], [1.825, 2.298, 0.457, 1.052, 0.655, 0.73], [-0.153, 1.778, 0.354, 0.514, 0.609, 0.42], [0.512, 1.223, 0.597, 0.407, 0.628, 0.692], [1.022, 1.172, 0.206, 0.702, 0.301, 0.176], [1.64, 0.74, 0.55, 0.197, 0.956, 0.52], [0.38, -0.727, 0.278, 0.877, 0.781, 0.837]]
Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.830629, 0.239867, -0.502514], [0.556756, 0.37214, -0.742654], [0.008867, -0.896647, -0.442658]]; the translation vector: [4.849209, 2.614689, 1.447477], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.442, -1.133, 0.562, 0.636, 0.657, 0.49], [-0.931, -0.023, 0.592, 0.548, 0.635, 0.449], [1.185, -0.67, 0.523, 0.55, 0.618, 0.447], [-0.778, 1.905, 0.84, 0.606, 0.538, 0.514], [-0.723, -1.153, 0.514, 0.657, 0.632, 0.473], [-1.434, -0.489, 0.591, 0.567, 0.545, 0.458], [-1.479, -1.704, 0.547, 0.555, 0.643, 0.506], [-1.06, 0.579, 0.646, 0.554, 0.57, 0.426], [1.728, -0.095, 0.592, 0.547, 0.596, 0.473], [-1.358, 1.889, 0.774, 0.643, 0.662, 0.446], [2.187, 1.992, 0.739, 0.592, 0.503, 0.463], [-0.349, 1.313, 0.568, 0.481, 0.31, 0.827], [0.659, 1.035, 0.643, 0.561, 0.458, 0.449], [1.351, 1.116, 0.663, 0.567, 0.545, 0.469], [1.67, 0.521, 0.73, 0.179, 0.508, 0.285], [0.482, -0.974, 0.492, 0.592, 0.586, 0.475]] B: [[-1.049, -1.529, 1.034, 0.201, 0.822, 0.539], [-0.9, 0.339, 0.327, 0.273, 0.766, 0.553], [0.737, -1.05, 0.211, 0.082, 0.504, 0.933], [-1.047, 2.226, 0.838, 0.996, 0.859, 0.972], [-0.719, -0.678, 0.784, 0.49, 0.145, 0.261], [-1.882, -0.392, 0.818, 0.955, 0.143, 0.713], [-1.551, -2.013, 0.366, 0.53, 0.75, 0.368], [-1.315, 0.463, 0.891, 0.81, 0.604, 0.638], [2.147, -0.334, 0.803, 0.499, 0.844, 0.692], [-1.677, 2.042, 0.864, 0.402, 1.157, 0.639], [1.976, 2.077, 0.904, 0.918, 0.711, 0.254], [-0.187, 1.603, 0.781, 0.267, -0.088, 1.027], [0.26, 0.795, 0.514, 0.847, -0.04, 0.297], [1.756, 1.456, 0.644, 0.597, 0.817, 0.47], [1.242, 0.068, 0.373, 0.448, 0.149, 0.381], [0.319, -0.553, 0.655, 0.691, 0.359, 0.589]] C: [[-0.988, -1.282, 0.732, 0.336, 0.483, 0.927], [-0.442, -0.073, 0.808, 0.229, 0.772, 0.639], [1.548, -1.036, 0.108, 0.525, 0.245, 0.035], [-1.266, 1.685, 1.335, 0.956, 0.747, 0.267], [-1.079, -1.607, 1.01, 0.83, 1.062, 0.521], [-1.264, -0.925, 0.343, 1.047, 0.715, 0.269], [-1.458, -1.958, 0.337, 0.66, 0.161, 0.546], [-0.733, 0.312, 0.474, 0.521, 0.178, -0.061], [2.105, 0.263, 0.727, 0.39, 0.976, 0.108], [-1.707, 1.787, 0.496, 0.472, 1.062, 0.821], [2.45, 1.544, 0.321, 1.018, 0.15, 0.075], [-0.837, 1.59, 0.268, 0.538, 0.245, 0.497], [0.297, 1.19, 0.423, 0.185, 0.686, 0.323], [0.857, 1.058, 0.937, 0.887, 0.209, 0.519], [1.802, 0.184, 0.797, 0.22, 0.094, 0.637], [0.094, -0.987, 0.725, 0.553, 1.059, 0.036]] D: [[-1.227, -0.819, 0.642, 0.301, 0.736, 0.894], [-1.335, 0.35, 0.132, 0.881, 0.202, 0.441], [1.374, -0.345, 0.698, 0.363, 1.089, 0.667], [-0.963, 1.843, 0.91, 0.493, 0.498, 0.35], [-1.186, -1.506, 0.169, 0.581, 0.638, 0.951], [-1.772, -0.025, 0.967, 0.473, 0.884, -0.032], [-1.614, -1.94, 0.374, 0.725, 0.441, 0.512], [-1.408, 0.285, 1.05, 0.486, 0.297, 0.835], [2.021, -0.535, 0.654, 0.219, 0.759, 0.901], [-1.57, 2.203, 0.527, 0.16, 0.291, 0.718], [1.825, 2.298, 0.457, 1.052, 0.655, 0.73], [-0.153, 1.778, 0.354, 0.514, 0.609, 0.42], [0.512, 1.223, 0.597, 0.407, 0.628, 0.692], [1.022, 1.172, 0.206, 0.702, 0.301, 0.176], [1.64, 0.74, 0.55, 0.197, 0.956, 0.52], [0.38, -0.727, 0.278, 0.877, 0.781, 0.837]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_172_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_172_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.285, 2.094, 0.223, 0.8, -0.126, 0.725], [0.89, 2.46, 0.447, -0.137, 0.338, 0.037]] B: [[0.378, 1.664, -0.029, 0.245, 0.007, 0.518], [0.551, 2.153, -0.045, 0.073, 0.825, 0.641]] C: [[0.842, 1.796, 0.181, 0.339, 0.338, 0.37], [0.768, 2.073, 0.205, 0.294, 0.394, 0.403]] D: [[0.562, 2.17, 0.079, 0.501, 0.638, 0.525], [0.42, 1.956, 0.647, 0.731, 0.278, 0.487]]
Given a RGB image and a depth image, please detect the 3D bounding box of the bucket in the scene. The camera pose information includes: the rotation matrix: [[-0.819759, -0.274444, 0.502669], [-0.572709, 0.39303, -0.719397], [-0.00013, -0.877615, -0.479366]]; the translation vector: [2.765326, 1.370172, 1.355227], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.285, 2.094, 0.223, 0.8, -0.126, 0.725], [0.89, 2.46, 0.447, -0.137, 0.338, 0.037]] B: [[0.378, 1.664, -0.029, 0.245, 0.007, 0.518], [0.551, 2.153, -0.045, 0.073, 0.825, 0.641]] C: [[0.842, 1.796, 0.181, 0.339, 0.338, 0.37], [0.768, 2.073, 0.205, 0.294, 0.394, 0.403]] D: [[0.562, 2.17, 0.079, 0.501, 0.638, 0.525], [0.42, 1.956, 0.647, 0.731, 0.278, 0.487]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_173_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_173_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.351, 1.709, 0.416, 3.301, 3.462, -0.205]] B: [[0.748, 1.385, 0.703, 3.676, 3.587, 0.247]] C: [[0.285, 1.079, 0.707, 4.151, 3.525, -0.098]] D: [[0.437, 1.63, 0.992, 3.864, 3.856, 0.472]]
Given a RGB image and a depth image, please detect the 3D bounding box of the table in the scene. The camera pose information includes: the rotation matrix: [[-0.119369, -0.433868, 0.893034], [-0.990549, 0.113242, -0.077387], [-0.067553, -0.893832, -0.443285]]; the translation vector: [3.407035, 4.679209, 1.397058], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.351, 1.709, 0.416, 3.301, 3.462, -0.205]] B: [[0.748, 1.385, 0.703, 3.676, 3.587, 0.247]] C: [[0.285, 1.079, 0.707, 4.151, 3.525, -0.098]] D: [[0.437, 1.63, 0.992, 3.864, 3.856, 0.472]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_174_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_174_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.171, -0.049, 0.811, 0.067, 1.74, 1.931], [2.378, 0.912, 0.851, 0.596, 2.524, 1.349], [0.415, -1.4, 0.688, 3.856, 0.243, 1.685], [2.428, -1.301, 0.364, 0.307, 0.039, 1.588], [-1.851, -0.771, 1.131, 0.437, 0.879, 1.981]] B: [[-2.124, 0.402, 0.972, 0.336, 1.814, 2.055], [2.714, 0.714, 0.306, -0.022, 2.698, 1.287], [0.218, -0.935, 0.625, 3.775, 0.411, 1.982], [2.74, -0.719, 0.42, -0.08, 0.24, 0.945], [-2.083, -0.772, 1.329, 0.652, 0.37, 2.117]] C: [[-2.229, 0.152, 1.164, 0.205, 1.859, 2.109], [2.442, 0.667, 0.678, 0.238, 2.976, 1.311], [0.131, -1.186, 0.807, 4.198, 0.217, 1.596], [2.311, -0.918, 0.648, 0.343, 0.478, 1.211], [-2.036, -0.925, 1.234, 0.571, 0.559, 1.867]] D: [[-2.234, 0.572, 0.912, 0.309, 1.595, 2.084], [2.569, 0.682, 1.117, -0.182, 2.613, 1.651], [-0.058, -0.811, 0.697, 4.093, -0.122, 2.058], [2.792, -1.246, 0.764, 0.753, 0.799, 0.76], [-1.948, -0.836, 1.559, 0.97, 0.14, 2.126]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.924746, 0.145405, -0.351715], [0.379908, 0.407811, -0.830277], [0.022707, -0.901414, -0.432362]]; the translation vector: [3.891577, 4.106122, 1.335216], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-2.171, -0.049, 0.811, 0.067, 1.74, 1.931], [2.378, 0.912, 0.851, 0.596, 2.524, 1.349], [0.415, -1.4, 0.688, 3.856, 0.243, 1.685], [2.428, -1.301, 0.364, 0.307, 0.039, 1.588], [-1.851, -0.771, 1.131, 0.437, 0.879, 1.981]] B: [[-2.124, 0.402, 0.972, 0.336, 1.814, 2.055], [2.714, 0.714, 0.306, -0.022, 2.698, 1.287], [0.218, -0.935, 0.625, 3.775, 0.411, 1.982], [2.74, -0.719, 0.42, -0.08, 0.24, 0.945], [-2.083, -0.772, 1.329, 0.652, 0.37, 2.117]] C: [[-2.229, 0.152, 1.164, 0.205, 1.859, 2.109], [2.442, 0.667, 0.678, 0.238, 2.976, 1.311], [0.131, -1.186, 0.807, 4.198, 0.217, 1.596], [2.311, -0.918, 0.648, 0.343, 0.478, 1.211], [-2.036, -0.925, 1.234, 0.571, 0.559, 1.867]] D: [[-2.234, 0.572, 0.912, 0.309, 1.595, 2.084], [2.569, 0.682, 1.117, -0.182, 2.613, 1.651], [-0.058, -0.811, 0.697, 4.093, -0.122, 2.058], [2.792, -1.246, 0.764, 0.753, 0.799, 0.76], [-1.948, -0.836, 1.559, 0.97, 0.14, 2.126]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_175_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_175_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.059, -1.275, 0.883, 0.298, 1.018, 2.01], [0.236, 1.462, 0.631, 0.873, 0.486, 1.281], [1.1, -1.001, 0.952, 1.349, 0.172, 2.338], [-0.839, 2.079, 0.96, 0.395, 0.842, 1.983], [1.955, -4.485, 1.036, 0.141, 0.98, 2.593], [-0.255, -0.481, 0.905, 0.161, 0.928, 1.969]] B: [[-0.954, -1.046, 0.462, 0.658, 0.618, 2.138], [-0.213, 1.899, 0.694, 0.708, 0.841, 1.686], [1.362, -1.133, 1.001, 1.465, -0.084, 2.501], [-0.862, 2.364, 0.854, 0.124, 0.853, 2.159], [2.413, -4.964, 0.774, -0.345, 1.16, 3.015], [0.156, -0.554, 0.434, -0.07, 0.695, 2.392]] C: [[-0.732, -1.166, 0.44, 0.739, 0.991, 1.593], [0.338, 1.95, 0.672, 0.941, 0.589, 1.757], [0.743, -0.963, 1.147, 1.448, -0.135, 2.517], [-1.129, 2.483, 1.375, 0.132, 1.054, 2.43], [1.587, -4.551, 0.847, 0.35, 0.965, 2.767], [-0.661, -0.507, 0.612, -0.243, 0.847, 1.515]] D: [[-0.907, -1.27, 0.42, -0.059, 1.138, 1.561], [0.626, 1.256, 1.105, 1.202, 0.216, 1.006], [0.877, -0.877, 1.149, 0.987, -0.045, 2.737], [-0.783, 1.691, 0.606, 0.081, 0.643, 2.205], [2.363, -4.049, 1.139, 0.229, 0.955, 2.439], [-0.196, -0.854, 0.721, 0.566, 0.583, 2.254]]
Given a RGB image and a depth image, please detect the 3D bounding box of the door in the scene. The camera pose information includes: the rotation matrix: [[-0.996429, -0.081152, -0.023325], [-0.01119, 0.400709, -0.916137], [0.083693, -0.912604, -0.400187]]; the translation vector: [7.365378, 2.610504, 1.343957], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.059, -1.275, 0.883, 0.298, 1.018, 2.01], [0.236, 1.462, 0.631, 0.873, 0.486, 1.281], [1.1, -1.001, 0.952, 1.349, 0.172, 2.338], [-0.839, 2.079, 0.96, 0.395, 0.842, 1.983], [1.955, -4.485, 1.036, 0.141, 0.98, 2.593], [-0.255, -0.481, 0.905, 0.161, 0.928, 1.969]] B: [[-0.954, -1.046, 0.462, 0.658, 0.618, 2.138], [-0.213, 1.899, 0.694, 0.708, 0.841, 1.686], [1.362, -1.133, 1.001, 1.465, -0.084, 2.501], [-0.862, 2.364, 0.854, 0.124, 0.853, 2.159], [2.413, -4.964, 0.774, -0.345, 1.16, 3.015], [0.156, -0.554, 0.434, -0.07, 0.695, 2.392]] C: [[-0.732, -1.166, 0.44, 0.739, 0.991, 1.593], [0.338, 1.95, 0.672, 0.941, 0.589, 1.757], [0.743, -0.963, 1.147, 1.448, -0.135, 2.517], [-1.129, 2.483, 1.375, 0.132, 1.054, 2.43], [1.587, -4.551, 0.847, 0.35, 0.965, 2.767], [-0.661, -0.507, 0.612, -0.243, 0.847, 1.515]] D: [[-0.907, -1.27, 0.42, -0.059, 1.138, 1.561], [0.626, 1.256, 1.105, 1.202, 0.216, 1.006], [0.877, -0.877, 1.149, 0.987, -0.045, 2.737], [-0.783, 1.691, 0.606, 0.081, 0.643, 2.205], [2.363, -4.049, 1.139, 0.229, 0.955, 2.439], [-0.196, -0.854, 0.721, 0.566, 0.583, 2.254]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_176_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_176_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.662, -1.551, 0.955, 1.174, 1.083, 1.423]] B: [[0.488, -1.177, 0.89, 1.089, 0.729, 1.751]] C: [[0.483, -0.736, 0.965, 0.958, 0.277, 1.886]] D: [[0.649, -1.283, 0.609, 1.143, 1.139, 2.193]]
Given a RGB image and a depth image, please detect the 3D bounding box of the desk in the scene. The camera pose information includes: the rotation matrix: [[0.51864, -0.44867, 0.727811], [-0.853934, -0.229463, 0.467059], [-0.04255, -0.863738, -0.502143]]; the translation vector: [1.002297, 1.98866, 1.344191], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.662, -1.551, 0.955, 1.174, 1.083, 1.423]] B: [[0.488, -1.177, 0.89, 1.089, 0.729, 1.751]] C: [[0.483, -0.736, 0.965, 0.958, 0.277, 1.886]] D: [[0.649, -1.283, 0.609, 1.143, 1.139, 2.193]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_177_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_177_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.285, -1.171, 0.463, 0.532, 0.611, 0.923], [1.223, 1.763, 0.56, 0.667, 0.631, 0.966], [-0.307, 1.833, 0.5, 0.619, 0.589, 0.922], [-0.406, -0.951, 0.39, 0.539, 0.611, 0.908], [0.655, 1.709, 0.525, 0.699, 0.634, 0.947], [1.269, -2.956, 0.836, 0.629, 0.557, 0.393], [1.192, 0.557, 0.457, 0.623, 0.615, 0.94], [0.416, -2.765, 0.677, 0.614, 0.452, 0.612], [-0.522, 0.635, 0.418, 0.585, 0.574, 0.905], [-0.363, -3.094, 0.495, 0.715, 0.612, 0.912], [0.336, 0.66, 0.438, 0.602, 0.623, 0.904], [-2.007, -0.347, 0.408, 0.521, 0.585, 0.891], [0.411, -1.036, 0.417, 0.682, 0.634, 0.922], [-2.039, -2.805, 0.495, 0.561, 0.631, 0.9], [-1.956, -1.834, 0.436, 0.597, 0.728, 0.922], [-2.754, 1.479, 0.509, 0.58, 0.603, 0.892]] B: [[0.94, -0.734, 0.86, 0.847, 0.174, 1.366], [1.047, 1.724, 0.337, 1.114, 0.725, 1.18], [-0.446, 1.839, 0.399, 1.0, 0.211, 0.928], [-0.224, -0.996, 0.671, 0.902, 0.396, 0.957], [0.648, 2.199, 0.865, 0.644, 0.899, 0.978], [1.601, -3.15, 1.071, 0.541, 0.264, 0.224], [0.709, 0.399, 0.396, 0.628, 0.643, 1.257], [0.103, -2.816, 0.184, 1.095, 0.871, 0.909], [-0.735, 1.113, 0.158, 0.968, 0.355, 1.244], [-0.793, -3.536, 0.957, 0.881, 0.306, 1.233], [-0.114, 0.863, 0.498, 0.236, 0.716, 1.116], [-1.845, -0.397, 0.53, 0.528, 0.958, 0.727], [0.156, -0.653, 0.083, 0.658, 1.129, 0.686], [-2.166, -2.74, 0.163, 0.166, 0.842, 0.447], [-2.421, -1.954, 0.206, 0.882, 0.734, 0.761], [-3.119, 1.809, 0.685, 0.543, 0.98, 1.284]] C: [[0.87, -1.386, 0.953, 0.148, 0.539, 1.241], [0.822, 1.276, 0.128, 0.239, 0.572, 1.227], [-0.508, 2.214, 0.373, 0.683, 0.2, 1.183], [-0.547, -1.349, -0.07, 0.231, 0.312, 1.389], [0.457, 1.367, 0.965, 0.768, 0.185, 1.088], [1.563, -2.649, 0.498, 0.756, 0.364, 0.362], [1.083, 0.345, 0.921, 0.769, 0.695, 1.386], [0.143, -3.095, 0.202, 0.278, 0.051, 0.502], [-0.474, 0.978, 0.872, 0.559, 0.082, 1.262], [-0.01, -3.401, 0.115, 1.005, 0.452, 1.143], [-0.106, 1.086, 0.284, 0.105, 0.131, 0.844], [-2.44, -0.304, -0.054, 0.667, 0.457, 0.703], [0.747, -1.031, -0.051, 0.551, 0.84, 0.909], [-2.101, -2.554, 0.473, 1.017, 0.994, 1.065], [-1.883, -2.033, 0.423, 0.644, 1.201, 0.726], [-3.109, 1.24, 0.812, 0.728, 1.099, 0.829]] D: [[1.585, -0.899, 0.099, 0.724, 0.912, 0.466], [0.799, 2.074, 0.967, 0.764, 0.821, 0.506], [-0.531, 1.393, 0.134, 0.737, 1.022, 1.024], [-0.008, -0.984, -0.095, 0.085, 0.528, 0.524], [0.362, 2.074, 0.189, 0.835, 0.387, 0.74], [1.446, -2.709, 0.927, 0.329, 0.916, 0.373], [1.078, 0.299, 0.482, 0.303, 0.612, 0.521], [0.439, -2.308, 0.3, 0.788, 0.517, 0.416], [-0.314, 0.386, 0.749, 0.588, 0.522, 1.244], [-0.739, -2.845, 0.766, 0.695, 1.017, 0.779], [-0.116, 0.704, 0.487, 0.148, 0.185, 0.776], [-1.607, 0.118, 0.862, 0.934, 0.609, 0.752], [-0.074, -0.593, 0.062, 0.851, 0.522, 0.762], [-2.188, -3.11, 0.134, 0.427, 0.414, 0.637], [-1.911, -1.906, 0.292, 0.873, 0.728, 0.955], [-2.793, 1.335, 0.084, 0.946, 0.494, 0.463]]
Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[0.931668, 0.072515, -0.356001], [0.362912, -0.231685, 0.902561], [-0.017031, -0.970084, -0.24217]]; the translation vector: [5.886859, 3.543659, 1.354971], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.285, -1.171, 0.463, 0.532, 0.611, 0.923], [1.223, 1.763, 0.56, 0.667, 0.631, 0.966], [-0.307, 1.833, 0.5, 0.619, 0.589, 0.922], [-0.406, -0.951, 0.39, 0.539, 0.611, 0.908], [0.655, 1.709, 0.525, 0.699, 0.634, 0.947], [1.269, -2.956, 0.836, 0.629, 0.557, 0.393], [1.192, 0.557, 0.457, 0.623, 0.615, 0.94], [0.416, -2.765, 0.677, 0.614, 0.452, 0.612], [-0.522, 0.635, 0.418, 0.585, 0.574, 0.905], [-0.363, -3.094, 0.495, 0.715, 0.612, 0.912], [0.336, 0.66, 0.438, 0.602, 0.623, 0.904], [-2.007, -0.347, 0.408, 0.521, 0.585, 0.891], [0.411, -1.036, 0.417, 0.682, 0.634, 0.922], [-2.039, -2.805, 0.495, 0.561, 0.631, 0.9], [-1.956, -1.834, 0.436, 0.597, 0.728, 0.922], [-2.754, 1.479, 0.509, 0.58, 0.603, 0.892]] B: [[0.94, -0.734, 0.86, 0.847, 0.174, 1.366], [1.047, 1.724, 0.337, 1.114, 0.725, 1.18], [-0.446, 1.839, 0.399, 1.0, 0.211, 0.928], [-0.224, -0.996, 0.671, 0.902, 0.396, 0.957], [0.648, 2.199, 0.865, 0.644, 0.899, 0.978], [1.601, -3.15, 1.071, 0.541, 0.264, 0.224], [0.709, 0.399, 0.396, 0.628, 0.643, 1.257], [0.103, -2.816, 0.184, 1.095, 0.871, 0.909], [-0.735, 1.113, 0.158, 0.968, 0.355, 1.244], [-0.793, -3.536, 0.957, 0.881, 0.306, 1.233], [-0.114, 0.863, 0.498, 0.236, 0.716, 1.116], [-1.845, -0.397, 0.53, 0.528, 0.958, 0.727], [0.156, -0.653, 0.083, 0.658, 1.129, 0.686], [-2.166, -2.74, 0.163, 0.166, 0.842, 0.447], [-2.421, -1.954, 0.206, 0.882, 0.734, 0.761], [-3.119, 1.809, 0.685, 0.543, 0.98, 1.284]] C: [[0.87, -1.386, 0.953, 0.148, 0.539, 1.241], [0.822, 1.276, 0.128, 0.239, 0.572, 1.227], [-0.508, 2.214, 0.373, 0.683, 0.2, 1.183], [-0.547, -1.349, -0.07, 0.231, 0.312, 1.389], [0.457, 1.367, 0.965, 0.768, 0.185, 1.088], [1.563, -2.649, 0.498, 0.756, 0.364, 0.362], [1.083, 0.345, 0.921, 0.769, 0.695, 1.386], [0.143, -3.095, 0.202, 0.278, 0.051, 0.502], [-0.474, 0.978, 0.872, 0.559, 0.082, 1.262], [-0.01, -3.401, 0.115, 1.005, 0.452, 1.143], [-0.106, 1.086, 0.284, 0.105, 0.131, 0.844], [-2.44, -0.304, -0.054, 0.667, 0.457, 0.703], [0.747, -1.031, -0.051, 0.551, 0.84, 0.909], [-2.101, -2.554, 0.473, 1.017, 0.994, 1.065], [-1.883, -2.033, 0.423, 0.644, 1.201, 0.726], [-3.109, 1.24, 0.812, 0.728, 1.099, 0.829]] D: [[1.585, -0.899, 0.099, 0.724, 0.912, 0.466], [0.799, 2.074, 0.967, 0.764, 0.821, 0.506], [-0.531, 1.393, 0.134, 0.737, 1.022, 1.024], [-0.008, -0.984, -0.095, 0.085, 0.528, 0.524], [0.362, 2.074, 0.189, 0.835, 0.387, 0.74], [1.446, -2.709, 0.927, 0.329, 0.916, 0.373], [1.078, 0.299, 0.482, 0.303, 0.612, 0.521], [0.439, -2.308, 0.3, 0.788, 0.517, 0.416], [-0.314, 0.386, 0.749, 0.588, 0.522, 1.244], [-0.739, -2.845, 0.766, 0.695, 1.017, 0.779], [-0.116, 0.704, 0.487, 0.148, 0.185, 0.776], [-1.607, 0.118, 0.862, 0.934, 0.609, 0.752], [-0.074, -0.593, 0.062, 0.851, 0.522, 0.762], [-2.188, -3.11, 0.134, 0.427, 0.414, 0.637], [-1.911, -1.906, 0.292, 0.873, 0.728, 0.955], [-2.793, 1.335, 0.084, 0.946, 0.494, 0.463]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_178_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_178_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.185, -1.981, 0.71, 1.746, 1.931, 1.092]] B: [[0.263, -1.622, 0.402, 1.389, 1.64, 0.804]] C: [[0.151, -1.735, 0.574, 1.767, 1.715, 0.631]] D: [[0.262, -2.035, 0.645, 1.006, 2.054, 1.049]]
Given a RGB image and a depth image, please detect the 3D bounding box of the table in the scene. The camera pose information includes: the rotation matrix: [[0.987126, 0.106622, -0.119219], [0.159938, -0.652529, 0.740693], [0.00118, -0.750225, -0.661181]]; the translation vector: [4.64166, 4.052867, 1.404314], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.185, -1.981, 0.71, 1.746, 1.931, 1.092]] B: [[0.263, -1.622, 0.402, 1.389, 1.64, 0.804]] C: [[0.151, -1.735, 0.574, 1.767, 1.715, 0.631]] D: [[0.262, -2.035, 0.645, 1.006, 2.054, 1.049]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_179_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_179_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.648, -0.593, 0.364, 0.758, 0.748, 0.835], [-1.189, -0.998, 0.388, 0.711, 0.664, 0.751], [-0.106, -0.14, 0.366, 0.681, 0.668, 0.806], [-0.467, -1.537, 0.381, 0.682, 0.66, 0.781]] B: [[0.715, -1.041, 0.651, 0.471, 0.834, 0.809], [-1.555, -0.972, 0.209, 0.39, 0.675, 1.08], [0.331, 0.337, 0.451, 0.906, 1.083, 1.138], [-0.367, -1.309, -0.086, 0.84, 1.029, 0.958]] C: [[0.76, -0.428, 0.328, 0.718, 0.602, 0.917], [-1.301, -1.169, 0.677, 0.824, 0.61, 0.712], [0.1, -0.045, 0.084, 0.878, 0.367, 0.431], [-0.14, -1.88, 0.43, 0.418, 0.474, 0.77]] D: [[0.587, -1.036, 0.299, 1.076, 1.171, 0.475], [-1.011, -1.458, 0.499, 0.276, 1.067, 0.759], [-0.487, -0.498, 0.17, 1.114, 0.58, 1.041], [-0.116, -1.819, 0.569, 0.961, 0.364, 1.204]]
Given a RGB image and a depth image, please detect the 3D bounding box of the armchair in the scene. The camera pose information includes: the rotation matrix: [[0.68967, 0.288211, -0.664297], [0.724122, -0.27239, 0.633602], [0.001663, -0.918008, -0.396559]]; the translation vector: [2.530043, 2.005069, 1.437417], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.648, -0.593, 0.364, 0.758, 0.748, 0.835], [-1.189, -0.998, 0.388, 0.711, 0.664, 0.751], [-0.106, -0.14, 0.366, 0.681, 0.668, 0.806], [-0.467, -1.537, 0.381, 0.682, 0.66, 0.781]] B: [[0.715, -1.041, 0.651, 0.471, 0.834, 0.809], [-1.555, -0.972, 0.209, 0.39, 0.675, 1.08], [0.331, 0.337, 0.451, 0.906, 1.083, 1.138], [-0.367, -1.309, -0.086, 0.84, 1.029, 0.958]] C: [[0.76, -0.428, 0.328, 0.718, 0.602, 0.917], [-1.301, -1.169, 0.677, 0.824, 0.61, 0.712], [0.1, -0.045, 0.084, 0.878, 0.367, 0.431], [-0.14, -1.88, 0.43, 0.418, 0.474, 0.77]] D: [[0.587, -1.036, 0.299, 1.076, 1.171, 0.475], [-1.011, -1.458, 0.499, 0.276, 1.067, 0.759], [-0.487, -0.498, 0.17, 1.114, 0.58, 1.041], [-0.116, -1.819, 0.569, 0.961, 0.364, 1.204]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_180_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_180_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.678, -1.667, 1.218, 1.055, -0.26, 2.418], [-1.464, 1.094, 0.83, 1.262, -0.304, 1.673], [0.614, 2.399, 0.708, 1.662, -0.241, 1.035], [0.965, -0.058, 1.477, 0.773, 4.136, 2.578], [-1.154, 1.558, 1.248, -0.057, 1.091, 2.617], [-1.717, -0.255, 1.603, -0.126, 2.491, 0.5]] B: [[-1.352, -1.046, 1.599, 1.44, 0.136, 2.792], [-1.654, 0.816, 0.791, 1.207, 0.132, 1.881], [0.521, 2.259, 1.273, 1.597, -0.332, 0.736], [0.806, 0.159, 1.62, 0.393, 4.568, 2.678], [-1.081, 1.507, 1.378, -0.253, 1.151, 2.742], [-1.495, -0.107, 1.278, 0.325, 1.906, 1.086]] C: [[-1.166, -1.418, 1.14, 1.061, 0.184, 2.392], [-1.606, 0.642, 1.143, 0.781, 0.159, 2.172], [0.167, 2.007, 1.118, 1.797, 0.138, 0.569], [0.908, -0.132, 1.206, 0.513, 4.305, 2.258], [-1.326, 1.1, 1.19, 0.242, 0.968, 2.282], [-1.838, -0.447, 1.348, 0.372, 2.121, 0.908]] D: [[-0.864, -1.506, 1.526, 0.637, 0.64, 2.228], [-1.745, 0.647, 0.899, 0.933, -0.243, 2.211], [-0.21, 1.507, 1.578, 2.065, 0.587, 0.484], [1.157, 0.294, 0.85, 0.968, 4.125, 2.603], [-1.113, 0.941, 1.165, 0.239, 0.756, 2.423], [-2.32, -0.87, 1.844, 0.517, 2.303, 0.518]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.964843, 0.186346, -0.185345], [0.252505, 0.461537, -0.850426], [-0.07293, -0.867329, -0.492364]]; the translation vector: [3.779865, 2.337391, 1.461827], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.678, -1.667, 1.218, 1.055, -0.26, 2.418], [-1.464, 1.094, 0.83, 1.262, -0.304, 1.673], [0.614, 2.399, 0.708, 1.662, -0.241, 1.035], [0.965, -0.058, 1.477, 0.773, 4.136, 2.578], [-1.154, 1.558, 1.248, -0.057, 1.091, 2.617], [-1.717, -0.255, 1.603, -0.126, 2.491, 0.5]] B: [[-1.352, -1.046, 1.599, 1.44, 0.136, 2.792], [-1.654, 0.816, 0.791, 1.207, 0.132, 1.881], [0.521, 2.259, 1.273, 1.597, -0.332, 0.736], [0.806, 0.159, 1.62, 0.393, 4.568, 2.678], [-1.081, 1.507, 1.378, -0.253, 1.151, 2.742], [-1.495, -0.107, 1.278, 0.325, 1.906, 1.086]] C: [[-1.166, -1.418, 1.14, 1.061, 0.184, 2.392], [-1.606, 0.642, 1.143, 0.781, 0.159, 2.172], [0.167, 2.007, 1.118, 1.797, 0.138, 0.569], [0.908, -0.132, 1.206, 0.513, 4.305, 2.258], [-1.326, 1.1, 1.19, 0.242, 0.968, 2.282], [-1.838, -0.447, 1.348, 0.372, 2.121, 0.908]] D: [[-0.864, -1.506, 1.526, 0.637, 0.64, 2.228], [-1.745, 0.647, 0.899, 0.933, -0.243, 2.211], [-0.21, 1.507, 1.578, 2.065, 0.587, 0.484], [1.157, 0.294, 0.85, 0.968, 4.125, 2.603], [-1.113, 0.941, 1.165, 0.239, 0.756, 2.423], [-2.32, -0.87, 1.844, 0.517, 2.303, 0.518]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_181_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_181_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.143, 1.32, 0.902, 0.946, 0.582, 0.814], [1.314, 2.961, 1.36, 1.125, 0.499, 2.359]] B: [[-1.164, 1.549, 1.101, 1.224, -0.166, 1.131], [1.215, 3.687, 1.039, 0.93, -0.333, 2.264]] C: [[-1.48, 1.652, 0.846, 0.755, 0.321, 1.167], [1.066, 3.327, 1.091, 1.04, 0.081, 1.998]] D: [[-1.81, 1.616, 0.892, 0.552, 0.779, 1.45], [1.382, 3.534, 1.284, 1.152, 0.521, 2.312]]
Given a RGB image and a depth image, please detect the 3D bounding box of the door in the scene. The camera pose information includes: the rotation matrix: [[-0.08083, -0.463089, 0.882618], [-0.994842, 0.091929, -0.042874], [-0.061284, -0.881531, -0.468131]]; the translation vector: [4.543997, 3.147744, 1.235262], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.143, 1.32, 0.902, 0.946, 0.582, 0.814], [1.314, 2.961, 1.36, 1.125, 0.499, 2.359]] B: [[-1.164, 1.549, 1.101, 1.224, -0.166, 1.131], [1.215, 3.687, 1.039, 0.93, -0.333, 2.264]] C: [[-1.48, 1.652, 0.846, 0.755, 0.321, 1.167], [1.066, 3.327, 1.091, 1.04, 0.081, 1.998]] D: [[-1.81, 1.616, 0.892, 0.552, 0.779, 1.45], [1.382, 3.534, 1.284, 1.152, 0.521, 2.312]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_182_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_182_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.277, 2.29, 0.603, 1.696, 0.522, 1.643], [-1.375, -0.321, 0.794, 0.343, 5.813, 1.671], [1.159, 0.472, 1.342, 0.486, 3.254, 0.972], [0.747, -2.391, 1.046, 0.652, 1.455, 1.87], [1.085, -1.961, 0.723, 1.174, -0.018, 1.576], [0.586, 1.92, 1.575, 0.646, -0.32, 2.439], [0.415, 2.748, 1.312, -0.384, 0.485, 2.051]] B: [[-0.351, 2.608, 0.955, 1.541, 0.097, 1.824], [-1.089, -0.096, 0.669, 0.099, 5.464, 1.395], [1.127, 0.133, 1.411, 0.212, 3.643, 0.932], [0.392, -2.442, 0.754, 0.163, 1.609, 1.541], [0.746, -1.664, 0.806, 0.833, 0.085, 1.637], [0.806, 1.971, 1.104, 0.829, 0.129, 2.13], [0.393, 2.271, 1.106, 0.064, 0.665, 2.126]] C: [[-0.013, 2.804, 0.64, 1.604, -0.241, 1.907], [-0.99, 0.257, 0.762, -0.167, 5.28, 1.868], [1.095, -0.318, 1.309, 0.698, 4.021, 0.652], [0.346, -2.805, 0.465, -0.167, 2.086, 1.213], [0.527, -1.307, 1.185, 0.733, -0.294, 1.468], [1.191, 1.911, 1.165, 0.69, 0.519, 1.853], [0.342, 2.498, 1.557, -0.047, 0.494, 2.435]] D: [[-0.612, 2.451, 1.013, 1.076, 0.146, 2.285], [-0.642, -0.043, 0.498, -0.353, 5.408, 1.585], [1.099, -0.043, 0.972, -0.204, 4.141, 1.05], [0.087, -2.832, 0.317, 0.167, 1.848, 1.113], [0.399, -1.498, 0.656, 1.117, 0.566, 1.989], [0.495, 2.449, 0.82, 0.411, 0.228, 2.522], [0.507, 2.378, 1.381, -0.184, 0.771, 1.769]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.286652, 0.220257, -0.932372], [0.958024, -0.061246, 0.28007], [0.004584, -0.973517, -0.228568]]; the translation vector: [3.76659, 1.676076, 1.452194], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.277, 2.29, 0.603, 1.696, 0.522, 1.643], [-1.375, -0.321, 0.794, 0.343, 5.813, 1.671], [1.159, 0.472, 1.342, 0.486, 3.254, 0.972], [0.747, -2.391, 1.046, 0.652, 1.455, 1.87], [1.085, -1.961, 0.723, 1.174, -0.018, 1.576], [0.586, 1.92, 1.575, 0.646, -0.32, 2.439], [0.415, 2.748, 1.312, -0.384, 0.485, 2.051]] B: [[-0.351, 2.608, 0.955, 1.541, 0.097, 1.824], [-1.089, -0.096, 0.669, 0.099, 5.464, 1.395], [1.127, 0.133, 1.411, 0.212, 3.643, 0.932], [0.392, -2.442, 0.754, 0.163, 1.609, 1.541], [0.746, -1.664, 0.806, 0.833, 0.085, 1.637], [0.806, 1.971, 1.104, 0.829, 0.129, 2.13], [0.393, 2.271, 1.106, 0.064, 0.665, 2.126]] C: [[-0.013, 2.804, 0.64, 1.604, -0.241, 1.907], [-0.99, 0.257, 0.762, -0.167, 5.28, 1.868], [1.095, -0.318, 1.309, 0.698, 4.021, 0.652], [0.346, -2.805, 0.465, -0.167, 2.086, 1.213], [0.527, -1.307, 1.185, 0.733, -0.294, 1.468], [1.191, 1.911, 1.165, 0.69, 0.519, 1.853], [0.342, 2.498, 1.557, -0.047, 0.494, 2.435]] D: [[-0.612, 2.451, 1.013, 1.076, 0.146, 2.285], [-0.642, -0.043, 0.498, -0.353, 5.408, 1.585], [1.099, -0.043, 0.972, -0.204, 4.141, 1.05], [0.087, -2.832, 0.317, 0.167, 1.848, 1.113], [0.399, -1.498, 0.656, 1.117, 0.566, 1.989], [0.495, 2.449, 0.82, 0.411, 0.228, 2.522], [0.507, 2.378, 1.381, -0.184, 0.771, 1.769]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_183_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_183_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.457, -0.683, 0.495, 0.679, 0.597, 0.903], [0.426, 0.843, 0.458, 0.566, 0.562, 0.949], [-0.336, 0.792, 0.461, 0.555, 0.539, 0.932], [0.926, -0.823, 0.62, 0.473, 0.568, 0.621], [-1.992, 0.348, 0.596, 0.635, 0.634, 0.647], [1.1, 0.858, 0.465, 0.529, 0.569, 0.952], [-0.253, -1.834, 0.689, 0.639, 0.561, 0.602], [-0.397, 2.119, 0.473, 0.759, 0.651, 0.94], [-1.254, -0.965, 0.657, 0.558, 0.592, 0.636], [-1.564, -0.168, 0.649, 0.462, 0.615, 0.611], [-0.169, -2.406, 0.711, 0.757, 0.669, 0.597], [1.375, -1.924, 0.508, 0.658, 0.509, 0.96], [0.214, -0.572, 0.651, 0.695, 0.494, 0.584], [-2.356, 2.053, 0.675, 0.673, 0.595, 0.536], [-0.799, -2.241, 0.541, 0.662, 0.673, 0.96], [1.941, -1.89, 0.718, 0.565, 0.56, 0.52], [2.571, -0.575, 0.472, 0.572, 0.595, 0.956], [-0.865, 2.028, 0.487, 0.583, 0.461, 0.128], [0.361, -2.459, 0.78, 0.536, 0.269, 0.489], [1.938, -1.474, 0.649, 0.57, 0.554, 0.6], [0.743, -2.15, 0.817, 0.526, 0.164, 0.344], [2.542, -1.129, 0.644, 0.598, 0.586, 0.612], [1.955, 0.145, 0.785, 0.141, 0.509, 0.304], [-1.685, 2.109, 0.449, 0.566, 0.486, 0.153], [-2.437, -1.918, 0.584, 0.515, 0.45, 0.203]] B: [[-0.004, -0.217, 0.058, 0.956, 0.104, 0.992], [0.634, 0.895, 0.282, 0.697, 0.893, 1.438], [-0.387, 0.349, 0.019, 0.239, 0.901, 0.96], [1.064, -1.168, 0.964, 0.374, 1.0, 0.253], [-1.606, 0.8, 0.112, 0.967, 0.862, 0.256], [1.288, 0.417, 0.225, 0.427, 0.112, 1.268], [-0.365, -1.988, 0.842, 0.932, 0.117, 0.21], [0.056, 2.617, 0.694, 0.602, 0.776, 0.848], [-1.173, -1.184, 0.2, 0.567, 0.839, 0.497], [-1.108, -0.485, 0.838, 0.382, 0.723, 1.057], [0.031, -2.18, 0.477, 1.078, 0.774, 0.574], [1.32, -1.614, 0.5, 0.512, 0.791, 1.227], [0.57, -1.002, 0.878, 0.861, 0.739, 0.347], [-2.072, 2.433, 1.143, 0.504, 1.054, 0.551], [-0.569, -2.64, 0.278, 0.616, 1.122, 1.078], [2.089, -1.691, 0.769, 0.97, 0.148, 0.992], [2.274, -0.687, 0.634, 0.56, 0.654, 0.811], [-1.223, 2.009, 0.495, 1.006, -0.028, 0.186], [0.145, -2.547, 0.54, 0.793, 0.387, 0.825], [1.744, -1.228, 0.533, 0.139, 0.886, 1.027], [1.123, -2.589, 1.183, 0.079, 0.187, 0.548], [2.235, -0.842, 0.485, 0.73, 0.575, 0.903], [1.694, -0.054, 1.249, 0.468, 0.557, 0.748], [-1.216, 2.107, 0.803, 0.764, 0.267, 0.274], [-2.623, -2.077, 1.01, 0.838, 0.106, -0.148]] C: [[-0.042, -0.277, 0.622, 0.349, 0.954, 1.11], [0.421, 0.801, 0.437, 0.094, 0.078, 1.2], [-0.436, 0.855, 0.625, 0.341, 0.737, 1.353], [0.599, -0.582, 0.28, 0.836, 0.717, 0.357], [-2.398, -0.135, 0.951, 0.429, 1.038, 0.502], [1.554, 0.709, 0.624, 0.144, 0.967, 1.304], [-0.666, -1.374, 0.422, 0.517, 0.122, 0.8], [-0.203, 1.908, 0.093, 1.027, 0.556, 0.76], [-1.532, -0.535, 0.437, 0.57, 0.41, 0.413], [-1.535, -0.307, 0.814, 0.936, 0.544, 1.082], [-0.39, -2.044, 0.309, 0.76, 0.801, 0.62], [1.044, -2.393, 0.932, 1.048, 0.287, 1.261], [0.664, -0.294, 1.14, 0.882, 0.176, 0.207], [-2.135, 2.211, 0.272, 0.963, 0.668, 0.76], [-1.028, -2.103, 1.016, 0.918, 0.609, 1.31], [1.579, -2.37, 0.458, 0.202, 0.159, 0.166], [2.079, -0.505, 0.945, 0.57, 0.86, 0.725], [-0.396, 2.379, 0.489, 0.77, 0.063, 0.52], [0.423, -2.492, 0.598, 0.788, 0.241, 0.406], [2.219, -1.548, 0.415, 0.429, 0.702, 0.329], [1.236, -1.961, 0.849, 0.371, 0.256, -0.039], [2.93, -1.099, 1.108, 0.393, 0.388, 0.187], [1.738, -0.099, 0.354, 0.013, 0.06, 0.667], [-1.711, 2.599, 0.36, 0.548, 0.69, -0.323], [-1.988, -1.796, 0.232, 0.609, 0.912, -0.043]] D: [[-0.117, -0.712, 0.165, 0.707, 0.749, 0.416], [0.663, 1.109, 0.92, 0.786, 0.382, 0.761], [-0.485, 1.276, -0.006, 0.122, 0.579, 0.562], [0.651, -1.033, 0.48, 0.012, 0.291, 0.281], [-1.67, 0.137, 0.785, 1.091, 0.142, 0.851], [1.44, 0.455, 0.476, 0.133, 0.572, 0.925], [-0.342, -1.74, 0.35, 0.646, 0.394, 0.443], [-0.793, 2.134, 0.146, 1.105, 0.456, 0.742], [-1.574, -0.65, 0.985, 0.2, 0.168, 1.102], [-1.526, 0.104, 0.427, 0.23, 0.555, 0.818], [-0.21, -2.447, 0.593, 1.166, 1.051, 0.465], [1.11, -2.085, 0.532, 0.952, 0.334, 0.936], [-0.231, -0.532, 0.895, 0.826, 0.523, 0.78], [-2.843, 1.728, 0.764, 0.92, 0.672, 0.101], [-0.845, -1.905, 0.458, 0.184, 0.635, 1.348], [1.844, -1.433, 1.033, 0.147, 0.968, 0.118], [2.166, -0.542, 0.733, 0.117, 0.957, 0.814], [-0.92, 1.743, 0.237, 0.993, 0.477, 0.227], [0.31, -2.458, 0.659, 0.782, 0.696, 0.669], [1.626, -1.353, 0.953, 0.579, 0.517, 0.513], [0.856, -2.414, 0.37, 0.927, 0.46, -0.04], [2.564, -1.512, 0.576, 0.167, 0.528, 0.323], [2.064, -0.007, 0.399, -0.022, 0.444, 0.68], [-1.281, 1.93, 0.706, 0.411, 0.266, -0.223], [-2.823, -2.037, 0.823, 0.649, 0.539, 0.078]]
Given a RGB image and a depth image, please detect the 3D bounding box of the chair in the scene. The camera pose information includes: the rotation matrix: [[-0.895509, 0.17248, -0.410263], [0.444823, 0.375965, -0.812886], [0.014038, -0.91044, -0.413402]]; the translation vector: [2.818061, 5.409916, 1.54775], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.457, -0.683, 0.495, 0.679, 0.597, 0.903], [0.426, 0.843, 0.458, 0.566, 0.562, 0.949], [-0.336, 0.792, 0.461, 0.555, 0.539, 0.932], [0.926, -0.823, 0.62, 0.473, 0.568, 0.621], [-1.992, 0.348, 0.596, 0.635, 0.634, 0.647], [1.1, 0.858, 0.465, 0.529, 0.569, 0.952], [-0.253, -1.834, 0.689, 0.639, 0.561, 0.602], [-0.397, 2.119, 0.473, 0.759, 0.651, 0.94], [-1.254, -0.965, 0.657, 0.558, 0.592, 0.636], [-1.564, -0.168, 0.649, 0.462, 0.615, 0.611], [-0.169, -2.406, 0.711, 0.757, 0.669, 0.597], [1.375, -1.924, 0.508, 0.658, 0.509, 0.96], [0.214, -0.572, 0.651, 0.695, 0.494, 0.584], [-2.356, 2.053, 0.675, 0.673, 0.595, 0.536], [-0.799, -2.241, 0.541, 0.662, 0.673, 0.96], [1.941, -1.89, 0.718, 0.565, 0.56, 0.52], [2.571, -0.575, 0.472, 0.572, 0.595, 0.956], [-0.865, 2.028, 0.487, 0.583, 0.461, 0.128], [0.361, -2.459, 0.78, 0.536, 0.269, 0.489], [1.938, -1.474, 0.649, 0.57, 0.554, 0.6], [0.743, -2.15, 0.817, 0.526, 0.164, 0.344], [2.542, -1.129, 0.644, 0.598, 0.586, 0.612], [1.955, 0.145, 0.785, 0.141, 0.509, 0.304], [-1.685, 2.109, 0.449, 0.566, 0.486, 0.153], [-2.437, -1.918, 0.584, 0.515, 0.45, 0.203]] B: [[-0.004, -0.217, 0.058, 0.956, 0.104, 0.992], [0.634, 0.895, 0.282, 0.697, 0.893, 1.438], [-0.387, 0.349, 0.019, 0.239, 0.901, 0.96], [1.064, -1.168, 0.964, 0.374, 1.0, 0.253], [-1.606, 0.8, 0.112, 0.967, 0.862, 0.256], [1.288, 0.417, 0.225, 0.427, 0.112, 1.268], [-0.365, -1.988, 0.842, 0.932, 0.117, 0.21], [0.056, 2.617, 0.694, 0.602, 0.776, 0.848], [-1.173, -1.184, 0.2, 0.567, 0.839, 0.497], [-1.108, -0.485, 0.838, 0.382, 0.723, 1.057], [0.031, -2.18, 0.477, 1.078, 0.774, 0.574], [1.32, -1.614, 0.5, 0.512, 0.791, 1.227], [0.57, -1.002, 0.878, 0.861, 0.739, 0.347], [-2.072, 2.433, 1.143, 0.504, 1.054, 0.551], [-0.569, -2.64, 0.278, 0.616, 1.122, 1.078], [2.089, -1.691, 0.769, 0.97, 0.148, 0.992], [2.274, -0.687, 0.634, 0.56, 0.654, 0.811], [-1.223, 2.009, 0.495, 1.006, -0.028, 0.186], [0.145, -2.547, 0.54, 0.793, 0.387, 0.825], [1.744, -1.228, 0.533, 0.139, 0.886, 1.027], [1.123, -2.589, 1.183, 0.079, 0.187, 0.548], [2.235, -0.842, 0.485, 0.73, 0.575, 0.903], [1.694, -0.054, 1.249, 0.468, 0.557, 0.748], [-1.216, 2.107, 0.803, 0.764, 0.267, 0.274], [-2.623, -2.077, 1.01, 0.838, 0.106, -0.148]] C: [[-0.042, -0.277, 0.622, 0.349, 0.954, 1.11], [0.421, 0.801, 0.437, 0.094, 0.078, 1.2], [-0.436, 0.855, 0.625, 0.341, 0.737, 1.353], [0.599, -0.582, 0.28, 0.836, 0.717, 0.357], [-2.398, -0.135, 0.951, 0.429, 1.038, 0.502], [1.554, 0.709, 0.624, 0.144, 0.967, 1.304], [-0.666, -1.374, 0.422, 0.517, 0.122, 0.8], [-0.203, 1.908, 0.093, 1.027, 0.556, 0.76], [-1.532, -0.535, 0.437, 0.57, 0.41, 0.413], [-1.535, -0.307, 0.814, 0.936, 0.544, 1.082], [-0.39, -2.044, 0.309, 0.76, 0.801, 0.62], [1.044, -2.393, 0.932, 1.048, 0.287, 1.261], [0.664, -0.294, 1.14, 0.882, 0.176, 0.207], [-2.135, 2.211, 0.272, 0.963, 0.668, 0.76], [-1.028, -2.103, 1.016, 0.918, 0.609, 1.31], [1.579, -2.37, 0.458, 0.202, 0.159, 0.166], [2.079, -0.505, 0.945, 0.57, 0.86, 0.725], [-0.396, 2.379, 0.489, 0.77, 0.063, 0.52], [0.423, -2.492, 0.598, 0.788, 0.241, 0.406], [2.219, -1.548, 0.415, 0.429, 0.702, 0.329], [1.236, -1.961, 0.849, 0.371, 0.256, -0.039], [2.93, -1.099, 1.108, 0.393, 0.388, 0.187], [1.738, -0.099, 0.354, 0.013, 0.06, 0.667], [-1.711, 2.599, 0.36, 0.548, 0.69, -0.323], [-1.988, -1.796, 0.232, 0.609, 0.912, -0.043]] D: [[-0.117, -0.712, 0.165, 0.707, 0.749, 0.416], [0.663, 1.109, 0.92, 0.786, 0.382, 0.761], [-0.485, 1.276, -0.006, 0.122, 0.579, 0.562], [0.651, -1.033, 0.48, 0.012, 0.291, 0.281], [-1.67, 0.137, 0.785, 1.091, 0.142, 0.851], [1.44, 0.455, 0.476, 0.133, 0.572, 0.925], [-0.342, -1.74, 0.35, 0.646, 0.394, 0.443], [-0.793, 2.134, 0.146, 1.105, 0.456, 0.742], [-1.574, -0.65, 0.985, 0.2, 0.168, 1.102], [-1.526, 0.104, 0.427, 0.23, 0.555, 0.818], [-0.21, -2.447, 0.593, 1.166, 1.051, 0.465], [1.11, -2.085, 0.532, 0.952, 0.334, 0.936], [-0.231, -0.532, 0.895, 0.826, 0.523, 0.78], [-2.843, 1.728, 0.764, 0.92, 0.672, 0.101], [-0.845, -1.905, 0.458, 0.184, 0.635, 1.348], [1.844, -1.433, 1.033, 0.147, 0.968, 0.118], [2.166, -0.542, 0.733, 0.117, 0.957, 0.814], [-0.92, 1.743, 0.237, 0.993, 0.477, 0.227], [0.31, -2.458, 0.659, 0.782, 0.696, 0.669], [1.626, -1.353, 0.953, 0.579, 0.517, 0.513], [0.856, -2.414, 0.37, 0.927, 0.46, -0.04], [2.564, -1.512, 0.576, 0.167, 0.528, 0.323], [2.064, -0.007, 0.399, -0.022, 0.444, 0.68], [-1.281, 1.93, 0.706, 0.411, 0.266, -0.223], [-2.823, -2.037, 0.823, 0.649, 0.539, 0.078]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_184_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_184_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.878, 0.793, 0.525, 0.307, 1.138, 0.24], [-1.741, 1.942, 0.919, 0.374, 0.284, 0.479], [-0.97, -1.167, 0.396, 0.145, 0.451, -0.19], [-1.083, -1.878, 0.816, 0.138, 0.403, 0.089], [-0.905, -1.314, 0.204, 0.196, 0.671, 0.614], [0.896, -0.37, -0.05, 0.065, 0.48, 0.052], [-0.311, 2.442, 0.913, 0.38, 0.489, 1.491]] B: [[-0.86, 0.987, 0.429, 0.753, 0.659, 0.935], [-1.179, 1.249, 1.101, 0.219, 0.461, 0.432], [-1.149, -1.648, 0.72, 0.293, 0.482, 0.205], [-0.806, -1.928, 1.378, 0.631, 0.665, 0.667], [-0.762, -1.463, 0.175, -0.154, 0.327, 0.058], [1.471, -0.937, 0.34, 0.631, 0.439, 0.05], [0.043, 1.928, 0.641, 0.637, 0.49, 0.81]] C: [[-0.458, 0.879, 0.858, 0.541, 0.86, 0.578], [-1.685, 1.754, 1.421, 0.241, 0.756, -0.241], [-1.527, -1.671, 0.922, 0.635, 0.013, 0.552], [-1.217, -1.15, 1.123, 0.142, 0.166, 0.441], [-1.042, -1.813, 0.54, 0.438, 0.445, 0.211], [1.239, -0.633, 0.179, 0.181, 0.23, 0.74], [-0.011, 2.472, 1.042, 0.129, 0.472, 1.438]] D: [[-0.55, 0.944, 0.644, 0.68, 1.046, 0.521], [-1.267, 1.712, 1.229, 0.359, 0.367, 0.165], [-1.24, -1.459, 0.828, 0.501, 0.283, 0.305], [-1.303, -1.553, 1.014, 0.399, 0.228, 0.178], [-0.73, -1.694, 0.629, 0.212, 0.251, 0.137], [1.337, -0.693, 0.283, 0.145, 0.467, 0.539], [0.135, 2.342, 0.574, 0.546, 0.62, 1.068]]
Given a RGB image and a depth image, please detect the 3D bounding box of the object in the scene. The camera pose information includes: the rotation matrix: [[0.330673, -0.328207, 0.884837], [-0.942686, -0.070458, 0.326157], [-0.044703, -0.941975, -0.332694]]; the translation vector: [3.753276, 4.481459, 1.345242], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.878, 0.793, 0.525, 0.307, 1.138, 0.24], [-1.741, 1.942, 0.919, 0.374, 0.284, 0.479], [-0.97, -1.167, 0.396, 0.145, 0.451, -0.19], [-1.083, -1.878, 0.816, 0.138, 0.403, 0.089], [-0.905, -1.314, 0.204, 0.196, 0.671, 0.614], [0.896, -0.37, -0.05, 0.065, 0.48, 0.052], [-0.311, 2.442, 0.913, 0.38, 0.489, 1.491]] B: [[-0.86, 0.987, 0.429, 0.753, 0.659, 0.935], [-1.179, 1.249, 1.101, 0.219, 0.461, 0.432], [-1.149, -1.648, 0.72, 0.293, 0.482, 0.205], [-0.806, -1.928, 1.378, 0.631, 0.665, 0.667], [-0.762, -1.463, 0.175, -0.154, 0.327, 0.058], [1.471, -0.937, 0.34, 0.631, 0.439, 0.05], [0.043, 1.928, 0.641, 0.637, 0.49, 0.81]] C: [[-0.458, 0.879, 0.858, 0.541, 0.86, 0.578], [-1.685, 1.754, 1.421, 0.241, 0.756, -0.241], [-1.527, -1.671, 0.922, 0.635, 0.013, 0.552], [-1.217, -1.15, 1.123, 0.142, 0.166, 0.441], [-1.042, -1.813, 0.54, 0.438, 0.445, 0.211], [1.239, -0.633, 0.179, 0.181, 0.23, 0.74], [-0.011, 2.472, 1.042, 0.129, 0.472, 1.438]] D: [[-0.55, 0.944, 0.644, 0.68, 1.046, 0.521], [-1.267, 1.712, 1.229, 0.359, 0.367, 0.165], [-1.24, -1.459, 0.828, 0.501, 0.283, 0.305], [-1.303, -1.553, 1.014, 0.399, 0.228, 0.178], [-0.73, -1.694, 0.629, 0.212, 0.251, 0.137], [1.337, -0.693, 0.283, 0.145, 0.467, 0.539], [0.135, 2.342, 0.574, 0.546, 0.62, 1.068]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_185_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_185_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.565, -1.185, 1.353, 0.464, 0.006, 0.118], [0.412, -0.591, 0.819, 0.036, 0.543, 0.322], [0.775, 0.247, 0.843, 0.919, 0.864, 0.389]] B: [[-0.648, -1.262, 0.922, 0.446, 0.433, 0.522], [0.437, -0.235, 0.949, 0.366, 0.445, 0.454], [0.764, 0.145, 0.941, 0.483, 0.409, 0.473]] C: [[-0.794, -1.422, 1.325, 0.646, -0.011, 0.511], [0.55, -0.124, 0.97, 0.767, 0.276, 0.151], [0.692, 0.134, 0.818, 0.04, 0.142, 0.775]] D: [[-0.888, -1.602, 1.373, 0.357, 0.797, 0.596], [0.014, -0.496, 0.808, 0.816, 0.004, 0.14], [0.932, 0.14, 0.871, 0.799, 0.355, 0.358]]
Given a RGB image and a depth image, please detect the 3D bounding box of the monitor in the scene. The camera pose information includes: the rotation matrix: [[0.054781, -0.427281, 0.902458], [-0.998013, -0.051617, 0.036143], [0.031139, -0.902644, -0.429259]]; the translation vector: [1.328526, 0.849821, 1.501181], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.565, -1.185, 1.353, 0.464, 0.006, 0.118], [0.412, -0.591, 0.819, 0.036, 0.543, 0.322], [0.775, 0.247, 0.843, 0.919, 0.864, 0.389]] B: [[-0.648, -1.262, 0.922, 0.446, 0.433, 0.522], [0.437, -0.235, 0.949, 0.366, 0.445, 0.454], [0.764, 0.145, 0.941, 0.483, 0.409, 0.473]] C: [[-0.794, -1.422, 1.325, 0.646, -0.011, 0.511], [0.55, -0.124, 0.97, 0.767, 0.276, 0.151], [0.692, 0.134, 0.818, 0.04, 0.142, 0.775]] D: [[-0.888, -1.602, 1.373, 0.357, 0.797, 0.596], [0.014, -0.496, 0.808, 0.816, 0.004, 0.14], [0.932, 0.14, 0.871, 0.799, 0.355, 0.358]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_186_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_186_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.353, -1.905, 0.542, 0.198, 0.811, 0.866]] B: [[-1.69, -2.015, 0.887, 0.014, 0.72, 0.41]] C: [[-1.178, -2.25, 0.868, 0.547, 0.466, 0.935]] D: [[-1.26, -1.838, 0.523, -0.212, 0.311, 0.619]]
Given a RGB image and a depth image, please detect the 3D bounding box of the dishwasher in the scene. The camera pose information includes: the rotation matrix: [[0.752445, 0.275595, -0.598225], [0.657828, -0.35994, 0.661593], [-0.032994, -0.891342, -0.452129]]; the translation vector: [2.633805, 2.70906, 1.31733], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.353, -1.905, 0.542, 0.198, 0.811, 0.866]] B: [[-1.69, -2.015, 0.887, 0.014, 0.72, 0.41]] C: [[-1.178, -2.25, 0.868, 0.547, 0.466, 0.935]] D: [[-1.26, -1.838, 0.523, -0.212, 0.311, 0.619]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_187_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_187_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.575, -1.33, 0.913, 0.422, 0.222, 1.282], [-1.133, -0.569, 0.691, 0.502, 1.733, 0.362], [-1.177, -0.378, 1.14, 0.427, 2.109, 0.616], [-1.073, 1.114, 1.403, 0.582, 1.219, 1.213], [-0.205, 1.471, 1.068, 1.327, 0.559, 1.11], [0.394, 0.971, 1.401, 0.368, 1.532, 0.97], [0.465, 0.918, 0.399, 0.657, 1.295, 0.944], [-1.033, 0.855, 0.494, 0.561, 0.838, 0.96]] B: [[0.612, -1.146, 1.029, 0.876, 0.249, 1.097], [-1.186, -0.558, 0.781, 0.832, 1.793, 0.11], [-0.68, -0.259, 1.327, 0.321, 2.085, 0.39], [-0.751, 1.462, 1.244, 1.064, 1.13, 1.071], [-0.245, 1.694, 1.448, 1.271, 0.405, 0.826], [0.501, 1.197, 1.032, 0.635, 1.295, 1.137], [0.575, 1.298, 0.738, 0.961, 1.68, 0.895], [-1.135, 0.586, 0.775, 0.711, 1.079, 0.526]] C: [[0.678, -1.206, 0.812, 0.848, -0.174, 1.369], [-1.023, -0.705, 0.492, 0.502, 1.434, -0.09], [-1.388, -0.068, 1.103, 0.59, 1.707, 0.559], [-1.152, 1.027, 1.347, 0.752, 0.971, 1.412], [-0.198, 1.443, 1.383, 1.532, 0.499, 1.267], [0.854, 0.79, 1.691, 0.351, 1.682, 0.641], [0.791, 0.546, 0.687, 0.219, 1.088, 1.252], [-0.634, 1.336, 0.286, 0.814, 1.197, 1.221]] D: [[0.82, -1.281, 0.96, -0.009, 0.662, 1.248], [-1.615, -0.505, 0.267, 0.866, 1.991, 0.496], [-0.964, -0.4, 1.176, 0.247, 2.442, 0.894], [-1.088, 1.358, 1.232, 0.782, 1.082, 0.821], [0.043, 1.718, 1.49, 1.508, 0.835, 1.275], [0.739, 1.084, 1.461, 0.376, 1.382, 1.444], [0.407, 0.623, 0.633, 0.434, 1.281, 1.107], [-1.311, 0.453, 0.839, 0.768, 1.093, 0.774]]
Given a RGB image and a depth image, please detect the 3D bounding box of the clothes in the scene. The camera pose information includes: the rotation matrix: [[0.88123, -0.188698, 0.433389], [-0.470321, -0.258404, 0.843816], [-0.047237, -0.947428, -0.316462]]; the translation vector: [1.061636, 1.321782, 1.457525], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.575, -1.33, 0.913, 0.422, 0.222, 1.282], [-1.133, -0.569, 0.691, 0.502, 1.733, 0.362], [-1.177, -0.378, 1.14, 0.427, 2.109, 0.616], [-1.073, 1.114, 1.403, 0.582, 1.219, 1.213], [-0.205, 1.471, 1.068, 1.327, 0.559, 1.11], [0.394, 0.971, 1.401, 0.368, 1.532, 0.97], [0.465, 0.918, 0.399, 0.657, 1.295, 0.944], [-1.033, 0.855, 0.494, 0.561, 0.838, 0.96]] B: [[0.612, -1.146, 1.029, 0.876, 0.249, 1.097], [-1.186, -0.558, 0.781, 0.832, 1.793, 0.11], [-0.68, -0.259, 1.327, 0.321, 2.085, 0.39], [-0.751, 1.462, 1.244, 1.064, 1.13, 1.071], [-0.245, 1.694, 1.448, 1.271, 0.405, 0.826], [0.501, 1.197, 1.032, 0.635, 1.295, 1.137], [0.575, 1.298, 0.738, 0.961, 1.68, 0.895], [-1.135, 0.586, 0.775, 0.711, 1.079, 0.526]] C: [[0.678, -1.206, 0.812, 0.848, -0.174, 1.369], [-1.023, -0.705, 0.492, 0.502, 1.434, -0.09], [-1.388, -0.068, 1.103, 0.59, 1.707, 0.559], [-1.152, 1.027, 1.347, 0.752, 0.971, 1.412], [-0.198, 1.443, 1.383, 1.532, 0.499, 1.267], [0.854, 0.79, 1.691, 0.351, 1.682, 0.641], [0.791, 0.546, 0.687, 0.219, 1.088, 1.252], [-0.634, 1.336, 0.286, 0.814, 1.197, 1.221]] D: [[0.82, -1.281, 0.96, -0.009, 0.662, 1.248], [-1.615, -0.505, 0.267, 0.866, 1.991, 0.496], [-0.964, -0.4, 1.176, 0.247, 2.442, 0.894], [-1.088, 1.358, 1.232, 0.782, 1.082, 0.821], [0.043, 1.718, 1.49, 1.508, 0.835, 1.275], [0.739, 1.084, 1.461, 0.376, 1.382, 1.444], [0.407, 0.623, 0.633, 0.434, 1.281, 1.107], [-1.311, 0.453, 0.839, 0.768, 1.093, 0.774]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_188_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_188_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.405, 0.601, 0.764, -0.233, 0.102, -0.396]] B: [[-1.074, 0.387, 1.003, 0.303, 0.098, -0.079]] C: [[-1.416, 1.278, 0.402, -0.026, 0.472, 0.541]] D: [[-1.238, 0.875, 0.853, 0.207, 0.18, 0.059]]
Given a RGB image and a depth image, please detect the 3D bounding box of the washcloth in the scene. The camera pose information includes: the rotation matrix: [[-0.922168, 0.178823, -0.342969], [0.38661, 0.453076, -0.803278], [0.011746, -0.873352, -0.486947]]; the translation vector: [3.207336, 1.959871, 1.267555], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.405, 0.601, 0.764, -0.233, 0.102, -0.396]] B: [[-1.074, 0.387, 1.003, 0.303, 0.098, -0.079]] C: [[-1.416, 1.278, 0.402, -0.026, 0.472, 0.541]] D: [[-1.238, 0.875, 0.853, 0.207, 0.18, 0.059]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_189_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_189_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.762, -1.555, 0.827, 2.184, 0.001, 1.66], [-1.543, -2.246, 0.687, 2.166, 0.538, 1.705], [-0.782, 1.874, 0.612, 0.36, -0.393, 2.288], [-2.462, 0.204, 1.234, 0.129, 3.712, 1.462], [-0.383, -1.635, 0.309, 0.432, -0.146, 1.237], [2.291, 0.002, 1.16, 0.467, 3.329, 1.816], [1.638, 1.427, 0.73, 2.104, 0.102, 1.563], [-1.67, 1.91, 0.562, 0.741, 0.507, 1.714]] B: [[1.374, -1.714, 0.725, 2.507, 0.169, 1.413], [-1.211, -1.757, 0.826, 2.443, 0.176, 1.694], [-0.519, 1.79, 0.908, 0.294, 0.099, 1.833], [-2.419, 0.035, 0.987, 0.337, 3.555, 1.874], [0.072, -1.69, 0.634, 0.2, 0.284, 1.225], [2.688, 0.023, 0.867, 0.191, 3.55, 1.732], [1.91, 1.763, 0.852, 1.655, 0.149, 1.762], [-2.022, 1.78, 0.984, 1.051, 0.126, 1.927]] C: [[0.908, -1.987, 1.173, 2.894, 0.341, 1.45], [-1.176, -1.625, 1.254, 2.938, 0.258, 1.218], [-0.734, 1.406, 1.146, 0.597, 0.342, 1.626], [-2.253, 0.34, 1.308, 0.063, 3.579, 1.568], [-0.079, -1.858, 0.689, 0.18, 0.741, 0.85], [2.904, 0.375, 0.691, 0.079, 3.103, 2.186], [1.824, 1.499, 0.728, 1.255, 0.079, 1.787], [-2.124, 1.899, 1.164, 1.019, 0.481, 1.863]] D: [[1.462, -1.527, 0.599, 2.871, 0.537, 1.876], [-0.801, -1.454, 1.05, 2.817, -0.258, 1.392], [-0.063, 2.202, 0.566, 0.693, 0.023, 1.708], [-2.869, -0.081, 1.48, 0.816, 3.209, 2.127], [0.07, -1.284, 0.825, -0.242, 0.304, 1.406], [2.798, 0.497, 1.202, 0.386, 3.591, 2.066], [1.458, 2.138, 0.37, 1.504, 0.6, 1.542], [-2.145, 1.824, 0.999, 1.206, 0.504, 1.867]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.984594, -0.069457, 0.160469], [-0.174127, -0.305795, 0.936039], [-0.015944, -0.949561, -0.313178]]; the translation vector: [3.941113, 2.817773, 1.559826], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.762, -1.555, 0.827, 2.184, 0.001, 1.66], [-1.543, -2.246, 0.687, 2.166, 0.538, 1.705], [-0.782, 1.874, 0.612, 0.36, -0.393, 2.288], [-2.462, 0.204, 1.234, 0.129, 3.712, 1.462], [-0.383, -1.635, 0.309, 0.432, -0.146, 1.237], [2.291, 0.002, 1.16, 0.467, 3.329, 1.816], [1.638, 1.427, 0.73, 2.104, 0.102, 1.563], [-1.67, 1.91, 0.562, 0.741, 0.507, 1.714]] B: [[1.374, -1.714, 0.725, 2.507, 0.169, 1.413], [-1.211, -1.757, 0.826, 2.443, 0.176, 1.694], [-0.519, 1.79, 0.908, 0.294, 0.099, 1.833], [-2.419, 0.035, 0.987, 0.337, 3.555, 1.874], [0.072, -1.69, 0.634, 0.2, 0.284, 1.225], [2.688, 0.023, 0.867, 0.191, 3.55, 1.732], [1.91, 1.763, 0.852, 1.655, 0.149, 1.762], [-2.022, 1.78, 0.984, 1.051, 0.126, 1.927]] C: [[0.908, -1.987, 1.173, 2.894, 0.341, 1.45], [-1.176, -1.625, 1.254, 2.938, 0.258, 1.218], [-0.734, 1.406, 1.146, 0.597, 0.342, 1.626], [-2.253, 0.34, 1.308, 0.063, 3.579, 1.568], [-0.079, -1.858, 0.689, 0.18, 0.741, 0.85], [2.904, 0.375, 0.691, 0.079, 3.103, 2.186], [1.824, 1.499, 0.728, 1.255, 0.079, 1.787], [-2.124, 1.899, 1.164, 1.019, 0.481, 1.863]] D: [[1.462, -1.527, 0.599, 2.871, 0.537, 1.876], [-0.801, -1.454, 1.05, 2.817, -0.258, 1.392], [-0.063, 2.202, 0.566, 0.693, 0.023, 1.708], [-2.869, -0.081, 1.48, 0.816, 3.209, 2.127], [0.07, -1.284, 0.825, -0.242, 0.304, 1.406], [2.798, 0.497, 1.202, 0.386, 3.591, 2.066], [1.458, 2.138, 0.37, 1.504, 0.6, 1.542], [-2.145, 1.824, 0.999, 1.206, 0.504, 1.867]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_190_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_190_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.548, -0.723, 1.702, 0.029, 0.56, 0.548], [0.99, -0.353, 1.798, 0.254, 0.406, 1.307], [0.157, -0.505, 0.811, 2.866, -0.08, 2.257], [-1.059, 0.22, 1.187, 0.204, 1.96, 1.609], [-1.515, 1.374, 1.432, 0.39, 0.462, 2.145], [-1.181, 2.329, 0.518, 0.161, 0.641, 1.327], [1.31, 1.368, 1.072, 1.078, 3.27, 1.707]] B: [[-0.408, -0.944, 1.285, 0.383, 0.855, 1.329], [1.037, -1.048, 1.113, 0.346, 0.92, 1.337], [0.631, -0.546, 1.683, 2.674, 0.421, 2.371], [-1.406, 0.284, 0.493, 0.426, 1.745, 1.616], [-0.913, 1.243, 0.625, 0.944, -0.159, 1.495], [-0.749, 1.827, 0.664, -0.223, 0.933, 1.793], [1.27, 1.253, 1.221, 0.403, 2.724, 2.094]] C: [[-0.454, -0.86, 2.026, 0.451, 0.358, 1.257], [1.65, -0.511, 2.057, 0.183, 0.13, 0.645], [0.357, -0.781, 1.143, 3.085, -0.312, 2.705], [-1.785, 0.873, 0.92, 0.414, 1.805, 1.915], [-0.907, 0.946, 0.648, 1.086, 0.063, 2.046], [-0.884, 1.711, 1.057, -0.048, 0.722, 0.964], [1.337, 0.641, 0.462, 0.296, 3.312, 2.01]] D: [[-0.751, -0.786, 1.574, 0.095, 0.444, 1.034], [1.18, -0.773, 1.574, 0.094, 0.433, 1.033], [0.142, -0.562, 1.184, 3.142, 0.116, 2.394], [-1.437, 0.419, 0.848, 0.139, 1.974, 1.688], [-1.083, 1.379, 1.042, 0.807, 0.163, 1.776], [-0.694, 1.837, 0.766, 0.107, 0.954, 1.459], [1.355, 0.889, 0.903, 0.788, 2.903, 1.82]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[-0.355681, -0.20797, 0.911175], [-0.934036, 0.113197, -0.338769], [-0.032689, -0.971563, -0.234514]]; the translation vector: [0.539195, 4.841905, 1.636959], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.548, -0.723, 1.702, 0.029, 0.56, 0.548], [0.99, -0.353, 1.798, 0.254, 0.406, 1.307], [0.157, -0.505, 0.811, 2.866, -0.08, 2.257], [-1.059, 0.22, 1.187, 0.204, 1.96, 1.609], [-1.515, 1.374, 1.432, 0.39, 0.462, 2.145], [-1.181, 2.329, 0.518, 0.161, 0.641, 1.327], [1.31, 1.368, 1.072, 1.078, 3.27, 1.707]] B: [[-0.408, -0.944, 1.285, 0.383, 0.855, 1.329], [1.037, -1.048, 1.113, 0.346, 0.92, 1.337], [0.631, -0.546, 1.683, 2.674, 0.421, 2.371], [-1.406, 0.284, 0.493, 0.426, 1.745, 1.616], [-0.913, 1.243, 0.625, 0.944, -0.159, 1.495], [-0.749, 1.827, 0.664, -0.223, 0.933, 1.793], [1.27, 1.253, 1.221, 0.403, 2.724, 2.094]] C: [[-0.454, -0.86, 2.026, 0.451, 0.358, 1.257], [1.65, -0.511, 2.057, 0.183, 0.13, 0.645], [0.357, -0.781, 1.143, 3.085, -0.312, 2.705], [-1.785, 0.873, 0.92, 0.414, 1.805, 1.915], [-0.907, 0.946, 0.648, 1.086, 0.063, 2.046], [-0.884, 1.711, 1.057, -0.048, 0.722, 0.964], [1.337, 0.641, 0.462, 0.296, 3.312, 2.01]] D: [[-0.751, -0.786, 1.574, 0.095, 0.444, 1.034], [1.18, -0.773, 1.574, 0.094, 0.433, 1.033], [0.142, -0.562, 1.184, 3.142, 0.116, 2.394], [-1.437, 0.419, 0.848, 0.139, 1.974, 1.688], [-1.083, 1.379, 1.042, 0.807, 0.163, 1.776], [-0.694, 1.837, 0.766, 0.107, 0.954, 1.459], [1.355, 0.889, 0.903, 0.788, 2.903, 1.82]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_191_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_191_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.515, -3.241, 1.128, 2.444, 0.863, 2.298], [1.577, 0.871, 1.235, 2.218, 0.709, 2.09], [1.099, 3.677, 1.424, 1.498, 0.813, 2.316], [1.686, -0.521, 1.08, 2.449, 0.774, 1.941], [1.48, 2.234, 1.312, 2.224, 0.696, 2.161], [0.71, 4.953, 0.833, 0.669, 0.644, 1.154], [1.678, -1.888, 1.095, 2.523, 0.759, 2.102]] B: [[1.269, -3.321, 1.076, 2.021, 0.959, 2.397], [1.664, 1.284, 1.204, 2.329, 1.065, 2.182], [1.189, 3.832, 1.394, 1.94, 1.033, 1.829], [2.066, -0.941, 0.589, 2.315, 1.169, 1.455], [1.915, 2.253, 1.321, 2.418, 0.57, 2.378], [0.213, 5.41, 0.898, 0.409, 1.093, 1.517], [1.55, -2.082, 1.024, 2.82, 0.884, 2.344]] C: [[1.118, -3.575, 0.993, 1.946, 0.682, 2.318], [1.412, 0.928, 1.006, 2.495, 0.73, 2.187], [0.774, 3.36, 0.968, 1.482, 0.922, 2.574], [1.295, -0.734, 1.167, 2.189, 0.383, 1.587], [1.325, 2.548, 0.999, 2.413, 1.015, 2.532], [0.98, 5.017, 0.875, 0.448, 0.455, 0.917], [2.018, -1.5, 1.046, 2.717, 0.819, 2.55]] D: [[1.259, -3.521, 1.143, 2.894, 0.867, 2.663], [1.362, 1.016, 1.431, 2.314, 0.878, 2.2], [0.748, 3.481, 1.025, 1.495, 1.271, 2.75], [1.85, -0.752, 1.348, 2.468, 0.657, 1.566], [1.513, 2.006, 1.345, 1.751, 0.827, 2.159], [0.635, 4.802, 1.263, 0.202, 1.111, 1.501], [1.353, -2.331, 1.563, 2.89, 1.228, 2.108]]
Given a RGB image and a depth image, please detect the 3D bounding box of the bookshelf in the scene. The camera pose information includes: the rotation matrix: [[-0.941243, -0.209403, 0.264975], [-0.336113, 0.504116, -0.795548], [0.033012, -0.837865, -0.544878]]; the translation vector: [4.828751, 9.008894, 1.463441], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.515, -3.241, 1.128, 2.444, 0.863, 2.298], [1.577, 0.871, 1.235, 2.218, 0.709, 2.09], [1.099, 3.677, 1.424, 1.498, 0.813, 2.316], [1.686, -0.521, 1.08, 2.449, 0.774, 1.941], [1.48, 2.234, 1.312, 2.224, 0.696, 2.161], [0.71, 4.953, 0.833, 0.669, 0.644, 1.154], [1.678, -1.888, 1.095, 2.523, 0.759, 2.102]] B: [[1.269, -3.321, 1.076, 2.021, 0.959, 2.397], [1.664, 1.284, 1.204, 2.329, 1.065, 2.182], [1.189, 3.832, 1.394, 1.94, 1.033, 1.829], [2.066, -0.941, 0.589, 2.315, 1.169, 1.455], [1.915, 2.253, 1.321, 2.418, 0.57, 2.378], [0.213, 5.41, 0.898, 0.409, 1.093, 1.517], [1.55, -2.082, 1.024, 2.82, 0.884, 2.344]] C: [[1.118, -3.575, 0.993, 1.946, 0.682, 2.318], [1.412, 0.928, 1.006, 2.495, 0.73, 2.187], [0.774, 3.36, 0.968, 1.482, 0.922, 2.574], [1.295, -0.734, 1.167, 2.189, 0.383, 1.587], [1.325, 2.548, 0.999, 2.413, 1.015, 2.532], [0.98, 5.017, 0.875, 0.448, 0.455, 0.917], [2.018, -1.5, 1.046, 2.717, 0.819, 2.55]] D: [[1.259, -3.521, 1.143, 2.894, 0.867, 2.663], [1.362, 1.016, 1.431, 2.314, 0.878, 2.2], [0.748, 3.481, 1.025, 1.495, 1.271, 2.75], [1.85, -0.752, 1.348, 2.468, 0.657, 1.566], [1.513, 2.006, 1.345, 1.751, 0.827, 2.159], [0.635, 4.802, 1.263, 0.202, 1.111, 1.501], [1.353, -2.331, 1.563, 2.89, 1.228, 2.108]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_192_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_192_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.126, -0.51, 1.73, -0.359, 0.479, 0.324]] B: [[-1.548, -0.135, 1.59, 0.021, 0.457, 0.386]] C: [[-1.508, -0.035, 1.589, -0.436, 0.071, 0.171]] D: [[-1.888, -0.563, 1.28, -0.393, 0.688, 0.046]]
Given a RGB image and a depth image, please detect the 3D bounding box of the picture in the scene. The camera pose information includes: the rotation matrix: [[0.623567, 0.536294, -0.568817], [0.781209, -0.455034, 0.427384], [-0.029628, -0.710867, -0.702702]]; the translation vector: [1.790477, 1.816361, 1.229059], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.126, -0.51, 1.73, -0.359, 0.479, 0.324]] B: [[-1.548, -0.135, 1.59, 0.021, 0.457, 0.386]] C: [[-1.508, -0.035, 1.589, -0.436, 0.071, 0.171]] D: [[-1.888, -0.563, 1.28, -0.393, 0.688, 0.046]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_193_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_193_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.08, 0.154, 1.005, 0.283, 1.414, 1.731]] B: [[-1.974, 0.286, 1.416, 0.341, 1.457, 1.235]] C: [[-1.941, 0.29, 1.24, -0.098, 1.307, 1.381]] D: [[-1.581, 0.374, 0.521, 0.311, 1.136, 1.526]]
Given a RGB image and a depth image, please detect the 3D bounding box of the whiteboard in the scene. The camera pose information includes: the rotation matrix: [[-0.341382, 0.594812, -0.727775], [0.932196, 0.11517, -0.343142], [-0.120287, -0.795572, -0.593798]]; the translation vector: [7.151203, 3.587152, 1.581923], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-2.08, 0.154, 1.005, 0.283, 1.414, 1.731]] B: [[-1.974, 0.286, 1.416, 0.341, 1.457, 1.235]] C: [[-1.941, 0.29, 1.24, -0.098, 1.307, 1.381]] D: [[-1.581, 0.374, 0.521, 0.311, 1.136, 1.526]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_194_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_194_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.65, 1.626, 0.952, 1.426, 0.125, 1.867]] B: [[-0.34, 1.647, 1.105, 1.036, 0.294, 2.092]] C: [[-0.202, 1.219, 1.248, 1.308, -0.28, 1.829]] D: [[-1.114, 1.711, 0.518, 0.996, 0.291, 2.172]]
Given a RGB image and a depth image, please detect the 3D bounding box of the doorframe in the scene. The camera pose information includes: the rotation matrix: [[-0.40936, -0.486807, 0.77165], [-0.912164, 0.236459, -0.334729], [-0.019515, -0.840896, -0.540844]]; the translation vector: [1.412713, 1.214489, 1.390939], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-0.65, 1.626, 0.952, 1.426, 0.125, 1.867]] B: [[-0.34, 1.647, 1.105, 1.036, 0.294, 2.092]] C: [[-0.202, 1.219, 1.248, 1.308, -0.28, 1.829]] D: [[-1.114, 1.711, 0.518, 0.996, 0.291, 2.172]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_195_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_195_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.253, 0.185, 0.949, 0.229, 3.97, 1.922], [-0.174, 1.794, 1.044, 2.121, 0.218, 2.116], [0.873, -0.38, 1.281, 0.158, 4.352, 2.497], [0.476, -2.537, 0.593, 0.677, 0.042, 1.129], [0.122, -2.616, 0.312, 0.063, 0.188, 0.596]] B: [[-1.703, -0.184, 0.581, -0.118, 3.494, 2.053], [0.248, 1.316, 1.102, 2.022, 0.319, 1.655], [1.35, -0.101, 1.108, 0.315, 4.473, 2.489], [0.441, -2.72, 0.688, 0.321, 0.469, 1.1], [-0.308, -2.248, -0.131, 0.362, 0.498, 0.335]] C: [[-1.001, 0.387, 0.855, 0.13, 4.223, 1.808], [-0.121, 2.25, 1.058, 2.216, 0.377, 2.185], [0.489, 0.025, 0.85, -0.341, 3.971, 2.77], [0.668, -2.895, 0.381, 0.972, 0.18, 1.122], [0.223, -2.648, 0.118, -0.29, 0.288, 0.814]] D: [[-1.615, 0.237, 0.631, 0.113, 3.734, 2.164], [-0.111, 1.6, 1.257, 2.2, 0.658, 1.704], [0.468, -0.376, 0.97, -0.134, 3.943, 2.668], [0.083, -2.476, 0.49, 0.836, 0.329, 1.629], [-0.101, -2.949, 0.022, 0.48, 0.426, 0.711]]
Given a RGB image and a depth image, please detect the 3D bounding box of the wall in the scene. The camera pose information includes: the rotation matrix: [[0.977514, -0.102294, 0.184398], [-0.210796, -0.497303, 0.841578], [0.005613, -0.861525, -0.507684]]; the translation vector: [3.555602, 1.207732, 1.356493], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[-1.253, 0.185, 0.949, 0.229, 3.97, 1.922], [-0.174, 1.794, 1.044, 2.121, 0.218, 2.116], [0.873, -0.38, 1.281, 0.158, 4.352, 2.497], [0.476, -2.537, 0.593, 0.677, 0.042, 1.129], [0.122, -2.616, 0.312, 0.063, 0.188, 0.596]] B: [[-1.703, -0.184, 0.581, -0.118, 3.494, 2.053], [0.248, 1.316, 1.102, 2.022, 0.319, 1.655], [1.35, -0.101, 1.108, 0.315, 4.473, 2.489], [0.441, -2.72, 0.688, 0.321, 0.469, 1.1], [-0.308, -2.248, -0.131, 0.362, 0.498, 0.335]] C: [[-1.001, 0.387, 0.855, 0.13, 4.223, 1.808], [-0.121, 2.25, 1.058, 2.216, 0.377, 2.185], [0.489, 0.025, 0.85, -0.341, 3.971, 2.77], [0.668, -2.895, 0.381, 0.972, 0.18, 1.122], [0.223, -2.648, 0.118, -0.29, 0.288, 0.814]] D: [[-1.615, 0.237, 0.631, 0.113, 3.734, 2.164], [-0.111, 1.6, 1.257, 2.2, 0.658, 1.704], [0.468, -0.376, 0.97, -0.134, 3.943, 2.668], [0.083, -2.476, 0.49, 0.836, 0.329, 1.629], [-0.101, -2.949, 0.022, 0.48, 0.426, 0.711]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_196_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_196_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.561, -0.516, 0.43, 0.03, 0.264, 0.023]] B: [[1.307, -0.077, 0.927, 0.18, 0.373, 0.438]] C: [[1.232, 0.339, 1.368, -0.266, 0.794, 0.386]] D: [[1.366, 0.134, 0.662, 0.477, 0.375, 0.57]]
Given a RGB image and a depth image, please detect the 3D bounding box of the toilet paper holder in the scene. The camera pose information includes: the rotation matrix: [[-0.566304, -0.590941, 0.574533], [-0.823945, 0.423135, -0.376925], [-0.020365, -0.686838, -0.726526]]; the translation vector: [2.143516, 1.760119, 1.343188], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[1.561, -0.516, 0.43, 0.03, 0.264, 0.023]] B: [[1.307, -0.077, 0.927, 0.18, 0.373, 0.438]] C: [[1.232, 0.339, 1.368, -0.266, 0.794, 0.386]] D: [[1.366, 0.134, 0.662, 0.477, 0.375, 0.57]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_197_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_197_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.989, -2.867, 2.62, 3.827, 5.879, 0.215]] B: [[0.557, -2.629, 2.447, 3.868, 5.161, -0.064]] C: [[0.767, -2.57, 3.32, 4.124, 4.999, -0.179]] D: [[0.538, -2.391, 2.899, 4.263, 5.407, 0.187]]
Given a RGB image and a depth image, please detect the 3D bounding box of the ceiling in the scene. The camera pose information includes: the rotation matrix: [[-0.999494, 0.005595, 0.031322], [-0.029883, 0.172936, -0.98448], [-0.010925, -0.984917, -0.172681]]; the translation vector: [6.687301, 5.436423, 1.742894], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.989, -2.867, 2.62, 3.827, 5.879, 0.215]] B: [[0.557, -2.629, 2.447, 3.868, 5.161, -0.064]] C: [[0.767, -2.57, 3.32, 4.124, 4.999, -0.179]] D: [[0.538, -2.391, 2.899, 4.263, 5.407, 0.187]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_198_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_198_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.728, -0.216, 1.391, -0.233, 0.319, 0.888]] B: [[1.382, -0.434, 1.41, 0.62, 0.036, 0.847]] C: [[1.017, -0.314, 0.963, 0.261, 0.326, 0.441]] D: [[1.373, -0.033, 0.749, 0.246, 0.609, 0.097]]
Given a RGB image and a depth image, please detect the 3D bounding box of the paper towel dispenser in the scene. The camera pose information includes: the rotation matrix: [[0.207705, 0.494542, -0.843971], [0.97739, -0.069996, 0.199524], [0.039599, -0.866331, -0.497898]]; the translation vector: [4.53083, 2.291093, 1.52739], representing the transformation from the camera coordinate system to the world coordinate system. For each detected object, provide the output in this format, i.e., [x, y, z, x_size, y_size, z_size]. Here, [x, y, z] represents the gravity center of the 3D bounding boxes in the world coordinate system, [x_size, y_size, z_size] represents the width, height, and length of the 3D bounding box.
Your task is to detect objects in 3D space using a scan of RGB-Depth image pair. Select from the following choices. A: [[0.728, -0.216, 1.391, -0.233, 0.319, 0.888]] B: [[1.382, -0.434, 1.41, 0.62, 0.036, 0.847]] C: [[1.017, -0.314, 0.963, 0.261, 0.326, 0.441]] D: [[1.373, -0.033, 0.749, 0.246, 0.609, 0.097]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_199_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_199_1.png" ]
C
Egocentric_Video_QuestionAnswering
egocentric image
EgoTaskQA
A: microwave B: refrigerator C: stove D: television
which object changed its status when the person do the first action did before he/she point to something?
Your task is to understand and reasoning about activities and events from the first-person perspective. Select from the following choices. A: microwave B: refrigerator C: stove D: television
[ "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_0.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_1.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_2.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_3.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_4.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_5.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_6.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_7.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_8.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_9.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_10.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_11.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_12.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_13.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_14.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_15.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_16.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_17.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_18.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_19.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_20.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_21.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_22.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_23.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_24.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_25.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_26.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_27.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_28.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_29.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_30.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_0_31.png" ]
C
Egocentric_Video_QuestionAnswering
egocentric image
EgoTaskQA
A: apple1 B: orange2 C: banana3 D: grape4
which object changed its status when the person put something to something?
Your task is to understand and reasoning about activities and events from the first-person perspective. Select from the following choices. A: apple1 B: orange2 C: banana3 D: grape4
[ "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_0.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_1.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_2.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_3.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_4.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_5.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_6.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_7.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_8.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_9.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_10.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_11.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_12.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_13.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_14.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_15.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_16.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_17.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_18.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_19.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_20.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_21.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_22.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_23.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_24.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_25.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_26.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_27.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_28.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_29.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_30.png", "./3D-spatial/Egocentric_Video_QuestionAnswering/Egocentric_Video_QuestionAnswering_1_31.png" ]
B