FanqingM
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MMIU-Benchmark
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threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.552, 0.743, 0.817, 1.009, -0.013, 1.113], [0.943, 1.174, 0.929, -0.18, 0.779, 1.068]] B: [[0.748, 0.782, 0.621, 0.556, 0.127, 0.839], [1.697, 1.131, 0.375, -0.273, 1.039, 1.495]] C: [[0.612, 1.202, 0.708, 0.529, 0.114, 0.821], [1.612, 1.184, 0.198, 0.419, 0.977, 0.647]] D: [[0.368, 1.181, 0.615, 0.989, 0.028, 1.271], [1.284, 0.726, 0.504, 0.067, 0.905, 1.037]]
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: [[-0.610102, 0.375008, -0.697958], [0.791763, 0.255448, -0.554849], [-0.029781, -0.891132, -0.452767]]; the translation vector: [2.349929, 1.419923, 1.358478], 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: [[0.552, 0.743, 0.817, 1.009, -0.013, 1.113], [0.943, 1.174, 0.929, -0.18, 0.779, 1.068]] B: [[0.748, 0.782, 0.621, 0.556, 0.127, 0.839], [1.697, 1.131, 0.375, -0.273, 1.039, 1.495]] C: [[0.612, 1.202, 0.708, 0.529, 0.114, 0.821], [1.612, 1.184, 0.198, 0.419, 0.977, 0.647]] D: [[0.368, 1.181, 0.615, 0.989, 0.028, 1.271], [1.284, 0.726, 0.504, 0.067, 0.905, 1.037]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_2_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_2_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.47, 0.453, 0.894, 0.2, 0.52, 0.291], [1.542, -0.676, 0.862, 0.217, 0.405, 0.289], [-1.666, -1.034, 0.158, 0.332, 0.363, 0.294]] B: [[1.471, 0.336, 1.375, -0.216, 0.786, 0.736], [1.469, -0.24, 1.152, 0.44, 0.255, 0.196], [-1.84, -1.112, 0.203, 0.586, 0.569, 0.159]] C: [[1.315, 0.861, 1.294, -0.145, 0.334, 0.615], [1.166, -0.686, 1.016, 0.2, 0.258, 0.346], [-2.029, -1.236, -0.071, 0.818, 0.37, 0.684]] D: [[1.59, 0.904, 1.331, 0.394, 0.302, 0.781], [1.626, -0.262, 1.266, -0.178, 0.337, 0.326], [-1.34, -1.047, 0.45, -0.149, 0.438, 0.179]]
Given a RGB image and a depth image, please detect the 3D bounding box of the speaker in the scene. The camera pose information includes: the rotation matrix: [[-0.283698, -0.38675, 0.877463], [-0.95878, 0.129662, -0.252839], [-0.015988, -0.913024, -0.407593]]; the translation vector: [3.69525, 3.551647, 1.352095], 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: [[1.47, 0.453, 0.894, 0.2, 0.52, 0.291], [1.542, -0.676, 0.862, 0.217, 0.405, 0.289], [-1.666, -1.034, 0.158, 0.332, 0.363, 0.294]] B: [[1.471, 0.336, 1.375, -0.216, 0.786, 0.736], [1.469, -0.24, 1.152, 0.44, 0.255, 0.196], [-1.84, -1.112, 0.203, 0.586, 0.569, 0.159]] C: [[1.315, 0.861, 1.294, -0.145, 0.334, 0.615], [1.166, -0.686, 1.016, 0.2, 0.258, 0.346], [-2.029, -1.236, -0.071, 0.818, 0.37, 0.684]] D: [[1.59, 0.904, 1.331, 0.394, 0.302, 0.781], [1.626, -0.262, 1.266, -0.178, 0.337, 0.326], [-1.34, -1.047, 0.45, -0.149, 0.438, 0.179]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_3_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_3_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.415, 0.474, 0.662, 0.608, 0.318, 0.607], [0.137, 1.366, 0.214, 0.809, 0.687, 0.563], [-0.119, -1.513, 0.412, 0.991, 0.469, 0.436], [0.958, -1.756, 0.374, 0.393, 0.461, 0.273]] B: [[0.097, 0.337, 0.367, 0.736, 0.669, 0.76], [-0.118, 0.915, 0.406, 0.54, 0.71, 0.78], [0.039, -1.273, 0.366, 0.52, 0.703, 0.787], [0.484, -2.107, 0.393, 0.516, 0.773, 0.731]] C: [[-0.145, 0.33, 0.215, 0.329, 0.397, 1.235], [-0.041, 1.377, -0.008, 0.173, 0.698, 1.043], [0.354, -0.822, 0.479, 0.306, 0.474, 0.987], [0.885, -2.559, 0.576, 0.548, 1.045, 0.546]] D: [[-0.062, 0.608, 0.646, 1.11, 1.056, 0.374], [0.266, 1.23, 0.893, 0.95, 0.801, 1.268], [-0.368, -1.641, 0.003, 0.257, 0.709, 0.427], [0.563, -2.189, 0.486, 0.531, 1.025, 0.714]]
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: [[-0.857694, 0.203115, -0.472341], [0.513544, 0.293426, -0.806333], [-0.025181, -0.934155, -0.355978]]; the translation vector: [3.161674, 3.662206, 1.335287], 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: [[0.415, 0.474, 0.662, 0.608, 0.318, 0.607], [0.137, 1.366, 0.214, 0.809, 0.687, 0.563], [-0.119, -1.513, 0.412, 0.991, 0.469, 0.436], [0.958, -1.756, 0.374, 0.393, 0.461, 0.273]] B: [[0.097, 0.337, 0.367, 0.736, 0.669, 0.76], [-0.118, 0.915, 0.406, 0.54, 0.71, 0.78], [0.039, -1.273, 0.366, 0.52, 0.703, 0.787], [0.484, -2.107, 0.393, 0.516, 0.773, 0.731]] C: [[-0.145, 0.33, 0.215, 0.329, 0.397, 1.235], [-0.041, 1.377, -0.008, 0.173, 0.698, 1.043], [0.354, -0.822, 0.479, 0.306, 0.474, 0.987], [0.885, -2.559, 0.576, 0.548, 1.045, 0.546]] D: [[-0.062, 0.608, 0.646, 1.11, 1.056, 0.374], [0.266, 1.23, 0.893, 0.95, 0.801, 1.268], [-0.368, -1.641, 0.003, 0.257, 0.709, 0.427], [0.563, -2.189, 0.486, 0.531, 1.025, 0.714]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_4_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_4_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.3, -0.383, 0.923, -0.356, 3.02, 2.635], [-2.115, 1.383, 0.841, 0.469, 0.927, 1.856], [-0.097, 1.484, 1.187, 3.044, -0.119, 1.807], [-1.377, 2.117, 0.899, -0.033, 1.21, 1.808], [1.159, -1.198, 1.874, 0.555, 0.176, 1.325]] B: [[1.941, -0.755, 1.598, -0.121, 2.674, 2.518], [-2.423, 1.211, 1.402, 0.192, 0.868, 2.164], [0.169, 1.203, 1.223, 2.673, -0.21, 2.157], [-1.688, 1.565, 0.939, 0.535, 1.926, 1.811], [1.734, -1.649, 1.385, 0.714, 0.109, 1.38]] C: [[1.696, -0.287, 1.129, 0.119, 2.8, 2.268], [-2.577, 1.535, 1.204, 0.613, 1.32, 2.198], [0.155, 1.133, 1.131, 3.032, 0.104, 2.204], [-1.285, 1.824, 1.154, 0.225, 1.437, 2.219], [1.488, -1.695, 1.419, 0.405, 0.098, 1.172]] D: [[1.453, -0.695, 1.348, 0.547, 3.272, 2.434], [-2.777, 1.417, 1.534, 1.007, 1.19, 1.834], [-0.034, 0.735, 1.208, 2.75, 0.551, 2.499], [-1.311, 1.97, 1.046, -0.151, 1.928, 1.721], [1.211, -2.136, 1.037, 0.829, -0.033, 1.518]]
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: [[0.199941, 0.263531, -0.943703], [0.979453, -0.027844, 0.19974], [0.026362, -0.964249, -0.263683]]; the translation vector: [3.611549, 3.757055, 1.562045], 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: [[1.3, -0.383, 0.923, -0.356, 3.02, 2.635], [-2.115, 1.383, 0.841, 0.469, 0.927, 1.856], [-0.097, 1.484, 1.187, 3.044, -0.119, 1.807], [-1.377, 2.117, 0.899, -0.033, 1.21, 1.808], [1.159, -1.198, 1.874, 0.555, 0.176, 1.325]] B: [[1.941, -0.755, 1.598, -0.121, 2.674, 2.518], [-2.423, 1.211, 1.402, 0.192, 0.868, 2.164], [0.169, 1.203, 1.223, 2.673, -0.21, 2.157], [-1.688, 1.565, 0.939, 0.535, 1.926, 1.811], [1.734, -1.649, 1.385, 0.714, 0.109, 1.38]] C: [[1.696, -0.287, 1.129, 0.119, 2.8, 2.268], [-2.577, 1.535, 1.204, 0.613, 1.32, 2.198], [0.155, 1.133, 1.131, 3.032, 0.104, 2.204], [-1.285, 1.824, 1.154, 0.225, 1.437, 2.219], [1.488, -1.695, 1.419, 0.405, 0.098, 1.172]] D: [[1.453, -0.695, 1.348, 0.547, 3.272, 2.434], [-2.777, 1.417, 1.534, 1.007, 1.19, 1.834], [-0.034, 0.735, 1.208, 2.75, 0.551, 2.499], [-1.311, 1.97, 1.046, -0.151, 1.928, 1.721], [1.211, -2.136, 1.037, 0.829, -0.033, 1.518]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_5_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_5_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.228, -1.379, 0.968, 0.05, 0.868, 0.876]] B: [[1.972, -1.363, 0.684, 0.094, 1.002, 1.369]] C: [[2.421, -1.068, 1.034, 0.177, 1.167, 1.478]] D: [[2.274, -1.598, 1.168, 0.52, 1.421, 1.228]]
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: [[-0.156961, 0.257294, -0.953501], [0.986843, 0.002956, -0.161652], [-0.038773, -0.966329, -0.254373]]; the translation vector: [1.838324, 1.205476, 1.480452], 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: [[2.228, -1.379, 0.968, 0.05, 0.868, 0.876]] B: [[1.972, -1.363, 0.684, 0.094, 1.002, 1.369]] C: [[2.421, -1.068, 1.034, 0.177, 1.167, 1.478]] D: [[2.274, -1.598, 1.168, 0.52, 1.421, 1.228]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_6_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_6_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.821, -1.627, 0.918, 0.317, 0.52, -0.34]] B: [[-1.196, -1.892, 0.539, 0.329, 0.374, 0.146]] C: [[-1.472, -2.353, 0.745, 0.703, 0.302, -0.352]] D: [[-1.33, -1.906, 0.911, -0.061, 0.797, -0.104]]
Given a RGB image and a depth image, please detect the 3D bounding box of the jacket in the scene. The camera pose information includes: the rotation matrix: [[0.999847, -0.004634, 0.01689], [-0.017397, -0.374134, 0.927211], [0.002023, -0.927363, -0.374157]]; the translation vector: [3.310194, 3.16458, 1.506432], 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: [[-0.821, -1.627, 0.918, 0.317, 0.52, -0.34]] B: [[-1.196, -1.892, 0.539, 0.329, 0.374, 0.146]] C: [[-1.472, -2.353, 0.745, 0.703, 0.302, -0.352]] D: [[-1.33, -1.906, 0.911, -0.061, 0.797, -0.104]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_7_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_7_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.441, 1.064, 0.78, 0.6, 1.194, 1.759]] B: [[0.806, 1.175, 0.723, 1.145, 0.857, 1.307]] C: [[1.47, 1.204, 0.738, 1.161, 1.149, 1.298]] D: [[1.013, 1.023, 0.774, 0.913, 1.329, 1.578]]
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: [[0.977181, 0.077241, -0.197866], [0.211774, -0.426158, 0.879512], [-0.016388, -0.901345, -0.432791]]; the translation vector: [0.977323, 0.877303, 1.40232], 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: [[1.441, 1.064, 0.78, 0.6, 1.194, 1.759]] B: [[0.806, 1.175, 0.723, 1.145, 0.857, 1.307]] C: [[1.47, 1.204, 0.738, 1.161, 1.149, 1.298]] D: [[1.013, 1.023, 0.774, 0.913, 1.329, 1.578]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_8_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_8_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.32, 0.548, 0.015, 3.907, 5.219, 0.432]] B: [[-0.869, 0.661, -0.307, 3.672, 4.614, -0.069]] C: [[-0.885, 0.436, 0.066, 3.44, 4.871, 0.305]] D: [[-1.228, 0.813, -0.025, 3.355, 4.94, 0.54]]
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: [[-0.30056, -0.511506, 0.805], [-0.953151, 0.130866, -0.272721], [0.034151, -0.849256, -0.526876]]; the translation vector: [-0.281614, 2.924112, 1.306122], 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: [[-1.32, 0.548, 0.015, 3.907, 5.219, 0.432]] B: [[-0.869, 0.661, -0.307, 3.672, 4.614, -0.069]] C: [[-0.885, 0.436, 0.066, 3.44, 4.871, 0.305]] D: [[-1.228, 0.813, -0.025, 3.355, 4.94, 0.54]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_9_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_9_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.236, 0.438, 2.571, 1.376, 1.585, 0.296]] B: [[0.105, 0.071, 2.209, 1.375, 1.269, -0.259]] C: [[-0.082, 0.088, 2.553, 1.257, 1.665, 0.102]] D: [[-0.566, -0.056, 2.979, 1.134, 1.904, -0.21]]
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: [[-0.255196, -0.436856, 0.862573], [-0.966393, 0.143834, -0.213066], [-0.030988, -0.887958, -0.45888]]; the translation vector: [1.734999, 0.744851, 1.432124], 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: [[0.236, 0.438, 2.571, 1.376, 1.585, 0.296]] B: [[0.105, 0.071, 2.209, 1.375, 1.269, -0.259]] C: [[-0.082, 0.088, 2.553, 1.257, 1.665, 0.102]] D: [[-0.566, -0.056, 2.979, 1.134, 1.904, -0.21]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_10_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_10_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.043, 0.444, 0.066, 3.645, 4.94, 0.241]] B: [[0.071, 0.025, -0.197, 3.897, 4.771, 0.696]] C: [[-0.523, 0.143, -0.403, 3.288, 4.973, 0.134]] D: [[0.378, 0.809, 0.444, 3.764, 4.725, 0.036]]
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: [[-0.436119, -0.427186, 0.79203], [-0.89981, 0.218659, -0.377532], [-0.011909, -0.877326, -0.479747]]; the translation vector: [1.992302, 3.72193, 1.553249], 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: [[-0.043, 0.444, 0.066, 3.645, 4.94, 0.241]] B: [[0.071, 0.025, -0.197, 3.897, 4.771, 0.696]] C: [[-0.523, 0.143, -0.403, 3.288, 4.973, 0.134]] D: [[0.378, 0.809, 0.444, 3.764, 4.725, 0.036]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_11_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_11_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.786, -1.469, 1.112, 0.86, 0.176, 1.647]] B: [[-0.914, -1.825, 1.495, 0.394, 0.281, 2.141]] C: [[-1.155, -1.563, 0.935, 0.81, 0.246, 1.235]] D: [[-0.398, -1.079, 1.275, 0.659, -0.007, 1.932]]
Given a RGB image and a depth image, please detect the 3D bounding box of the curtain in the scene. The camera pose information includes: the rotation matrix: [[-0.112591, -0.547395, 0.829266], [-0.992672, 0.098819, -0.069547], [-0.043877, -0.83102, -0.55451]]; the translation vector: [1.18498, 1.814175, 1.496605], 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: [[-0.786, -1.469, 1.112, 0.86, 0.176, 1.647]] B: [[-0.914, -1.825, 1.495, 0.394, 0.281, 2.141]] C: [[-1.155, -1.563, 0.935, 0.81, 0.246, 1.235]] D: [[-0.398, -1.079, 1.275, 0.659, -0.007, 1.932]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_12_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_12_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.187, -2.136, 1.49, 0.407, 0.4, 0.612], [0.6, -1.205, 1.939, 0.176, 0.133, -0.205]] B: [[0.434, -1.704, 1.717, 0.327, 0.549, 0.278], [0.752, -1.616, 1.803, 0.403, 0.362, 0.211]] C: [[0.158, -1.92, 1.36, -0.055, 0.096, 0.484], [0.44, -1.879, 1.563, 0.594, 0.374, 0.673]] D: [[-0.017, -1.973, 1.957, -0.127, 0.324, 0.483], [0.88, -1.365, 2.154, 0.664, 0.083, -0.049]]
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: [[0.645842, -0.099101, 0.757012], [-0.761541, -0.013148, 0.647984], [-0.054263, -0.994991, -0.083961]]; the translation vector: [3.729951, 1.432448, 1.733539], 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: [[0.187, -2.136, 1.49, 0.407, 0.4, 0.612], [0.6, -1.205, 1.939, 0.176, 0.133, -0.205]] B: [[0.434, -1.704, 1.717, 0.327, 0.549, 0.278], [0.752, -1.616, 1.803, 0.403, 0.362, 0.211]] C: [[0.158, -1.92, 1.36, -0.055, 0.096, 0.484], [0.44, -1.879, 1.563, 0.594, 0.374, 0.673]] D: [[-0.017, -1.973, 1.957, -0.127, 0.324, 0.483], [0.88, -1.365, 2.154, 0.664, 0.083, -0.049]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_13_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_13_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.798, -1.611, 1.132, 0.285, 0.531, 1.165]] B: [[1.687, -1.332, 1.2, 0.199, 0.988, 0.799]] C: [[1.357, -0.901, 1.518, -0.194, 0.606, 1.017]] D: [[1.876, -1.168, 0.737, 0.277, 1.058, 1.074]]
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: [[0.14018, 0.443083, -0.885453], [0.989985, -0.07783, 0.117782], [-0.016727, -0.893096, -0.449556]]; the translation vector: [3.549726, 0.935059, 1.485921], 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: [[1.798, -1.611, 1.132, 0.285, 0.531, 1.165]] B: [[1.687, -1.332, 1.2, 0.199, 0.988, 0.799]] C: [[1.357, -0.901, 1.518, -0.194, 0.606, 1.017]] D: [[1.876, -1.168, 0.737, 0.277, 1.058, 1.074]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_14_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_14_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.819, -0.006, 0.434, 0.452, 1.821, 0.691], [-2.563, 0.098, 0.464, 0.939, 2.679, 0.721]] B: [[-1.198, -0.018, -0.225, 0.953, 2.14, 0.57], [-3.038, 0.583, 0.16, 0.212, 2.66, 1.39]] C: [[-1.115, -0.366, 0.124, 1.037, 1.922, 0.126], [-3.074, 0.098, -0.014, 0.214, 2.71, 0.451]] D: [[-0.889, -0.312, 0.236, 0.943, 2.266, 0.443], [-3.042, 0.305, 0.458, 0.511, 3.034, 0.927]]
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: [[0.988959, -0.006087, -0.148062], [0.148117, 0.009943, 0.98892], [-0.004548, -0.999932, 0.010735]]; the translation vector: [3.911582, 2.672538, 1.565046], 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: [[-0.819, -0.006, 0.434, 0.452, 1.821, 0.691], [-2.563, 0.098, 0.464, 0.939, 2.679, 0.721]] B: [[-1.198, -0.018, -0.225, 0.953, 2.14, 0.57], [-3.038, 0.583, 0.16, 0.212, 2.66, 1.39]] C: [[-1.115, -0.366, 0.124, 1.037, 1.922, 0.126], [-3.074, 0.098, -0.014, 0.214, 2.71, 0.451]] D: [[-0.889, -0.312, 0.236, 0.943, 2.266, 0.443], [-3.042, 0.305, 0.458, 0.511, 3.034, 0.927]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_15_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_15_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.003, 1.71, 2.094, 0.541, 0.263, 0.118], [1.203, 1.68, 0.477, 1.133, 0.414, 1.172]] B: [[1.233, 1.735, 1.724, 0.591, 0.58, 0.487], [0.701, 1.63, 0.882, 0.862, 0.077, 0.96]] C: [[0.897, 1.469, 2.006, 0.732, 0.251, 0.23], [0.896, 1.321, 0.509, 1.078, 0.563, 0.956]] D: [[1.067, 1.911, 1.889, 0.58, 0.392, -0.26], [1.382, 1.503, 0.381, 1.083, 0.31, 0.478]]
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: [[-0.767458, -0.265442, 0.583565], [-0.640543, 0.35536, -0.680752], [-0.026676, -0.896248, -0.442751]]; the translation vector: [3.343537, 3.697402, 1.375352], 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: [[1.003, 1.71, 2.094, 0.541, 0.263, 0.118], [1.203, 1.68, 0.477, 1.133, 0.414, 1.172]] B: [[1.233, 1.735, 1.724, 0.591, 0.58, 0.487], [0.701, 1.63, 0.882, 0.862, 0.077, 0.96]] C: [[0.897, 1.469, 2.006, 0.732, 0.251, 0.23], [0.896, 1.321, 0.509, 1.078, 0.563, 0.956]] D: [[1.067, 1.911, 1.889, 0.58, 0.392, -0.26], [1.382, 1.503, 0.381, 1.083, 0.31, 0.478]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_16_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_16_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.138, 0.124, 0.676, -0.24, 4.388, 1.6], [-0.991, 0.479, 1.092, 0.412, 4.521, 1.772], [0.357, 1.729, 0.48, 2.481, 0.664, 1.17]] B: [[1.22, 0.284, 0.605, 0.161, 4.409, 2.133], [-1.442, 0.481, 1.313, -0.024, 4.063, 1.777], [-0.203, 2.498, 0.224, 1.968, 0.299, 1.17]] C: [[0.938, 0.113, 0.929, -0.179, 3.724, 1.454], [-0.685, 0.25, 0.853, -0.017, 3.941, 2.536], [-0.076, 2.502, 0.394, 2.11, -0.271, 0.712]] D: [[1.264, 0.297, 0.846, 0.212, 3.931, 1.71], [-1.088, 0.197, 1.004, 0.293, 4.063, 2.062], [0.059, 2.138, 0.489, 2.4, 0.176, 0.937]]
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: [[-0.311411, -0.45253, 0.835607], [-0.948656, 0.199362, -0.245576], [-0.055457, -0.869179, -0.491379]]; the translation vector: [2.299133, 2.388773, 1.459468], 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: [[1.138, 0.124, 0.676, -0.24, 4.388, 1.6], [-0.991, 0.479, 1.092, 0.412, 4.521, 1.772], [0.357, 1.729, 0.48, 2.481, 0.664, 1.17]] B: [[1.22, 0.284, 0.605, 0.161, 4.409, 2.133], [-1.442, 0.481, 1.313, -0.024, 4.063, 1.777], [-0.203, 2.498, 0.224, 1.968, 0.299, 1.17]] C: [[0.938, 0.113, 0.929, -0.179, 3.724, 1.454], [-0.685, 0.25, 0.853, -0.017, 3.941, 2.536], [-0.076, 2.502, 0.394, 2.11, -0.271, 0.712]] D: [[1.264, 0.297, 0.846, 0.212, 3.931, 1.71], [-1.088, 0.197, 1.004, 0.293, 4.063, 2.062], [0.059, 2.138, 0.489, 2.4, 0.176, 0.937]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_17_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_17_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.286, 0.023, 0.43, 0.149, 0.955, 0.837], [-1.223, 1.506, 0.654, 0.172, 1.002, 1.099]] B: [[-1.716, 0.263, -0.049, 0.591, 1.354, 0.711], [-1.546, 1.706, 0.156, 0.078, 0.869, 0.807]] C: [[-0.94, -0.207, 0.36, 0.417, 1.226, 0.947], [-1.061, 1.683, 0.653, 0.491, 0.617, 1.297]] D: [[-1.505, -0.176, 0.438, -0.283, 0.675, 1.3], [-1.566, 1.679, 1.013, -0.274, 0.726, 0.998]]
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: [[-0.305635, -0.390507, 0.868385], [-0.952144, 0.122302, -0.280116], [0.003183, -0.91244, -0.409198]]; the translation vector: [4.266061, 1.773856, 1.285079], 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: [[-1.286, 0.023, 0.43, 0.149, 0.955, 0.837], [-1.223, 1.506, 0.654, 0.172, 1.002, 1.099]] B: [[-1.716, 0.263, -0.049, 0.591, 1.354, 0.711], [-1.546, 1.706, 0.156, 0.078, 0.869, 0.807]] C: [[-0.94, -0.207, 0.36, 0.417, 1.226, 0.947], [-1.061, 1.683, 0.653, 0.491, 0.617, 1.297]] D: [[-1.505, -0.176, 0.438, -0.283, 0.675, 1.3], [-1.566, 1.679, 1.013, -0.274, 0.726, 0.998]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_18_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_18_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.301, -0.248, -0.183, 3.399, 5.209, 0.282]] B: [[0.089, -0.015, -0.009, 3.337, 5.518, 0.258]] C: [[0.396, -0.159, 0.362, 3.257, 5.951, -0.2]] D: [[0.093, 0.115, -0.474, 3.284, 5.168, 0.122]]
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: [[-0.934582, -0.143102, 0.325696], [-0.355737, 0.383069, -0.852473], [-0.002774, -0.912568, -0.408916]]; the translation vector: [2.694367, 2.483235, 1.465763], 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: [[-0.301, -0.248, -0.183, 3.399, 5.209, 0.282]] B: [[0.089, -0.015, -0.009, 3.337, 5.518, 0.258]] C: [[0.396, -0.159, 0.362, 3.257, 5.951, -0.2]] D: [[0.093, 0.115, -0.474, 3.284, 5.168, 0.122]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_19_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_19_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.264, 0.68, 0.463, 0.725, 0.55, 0.967], [1.225, 0.142, 2.156, 0.68, 2.62, 0.669]] B: [[0.179, 0.182, 0.661, 0.23, 1.022, 0.617], [1.51, -0.031, 1.909, 0.955, 2.219, 0.647]] C: [[0.069, 0.653, 0.766, 0.622, 0.263, 0.911], [0.908, 0.073, 1.898, 0.615, 2.442, 0.579]] D: [[-0.094, 1.133, 0.833, 0.562, 0.551, 0.493], [1.073, 0.074, 2.645, 0.407, 2.814, 0.994]]
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: [[-0.928375, -0.17783, 0.326339], [-0.371449, 0.415395, -0.830345], [0.012101, -0.892089, -0.451697]]; the translation vector: [2.096006, 1.919092, 1.36174], 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: [[-0.264, 0.68, 0.463, 0.725, 0.55, 0.967], [1.225, 0.142, 2.156, 0.68, 2.62, 0.669]] B: [[0.179, 0.182, 0.661, 0.23, 1.022, 0.617], [1.51, -0.031, 1.909, 0.955, 2.219, 0.647]] C: [[0.069, 0.653, 0.766, 0.622, 0.263, 0.911], [0.908, 0.073, 1.898, 0.615, 2.442, 0.579]] D: [[-0.094, 1.133, 0.833, 0.562, 0.551, 0.493], [1.073, 0.074, 2.645, 0.407, 2.814, 0.994]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_20_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_20_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.718, -0.44, 1.96, 0.228, 0.897, 0.293], [-1.706, -1.293, 1.868, 0.22, 0.846, 0.362], [-1.707, -1.314, 0.762, 0.375, 0.826, 0.302], [-1.691, 1.543, 1.626, 0.337, 0.697, 0.437], [-1.573, 1.406, 1.291, 0.181, 0.564, 0.313]] B: [[-1.988, -0.706, 1.585, 0.615, 0.861, 0.547], [-1.403, -1.309, 1.785, -0.129, 1.049, -0.092], [-1.749, -1.25, 0.92, 0.869, 1.088, 0.428], [-1.92, 1.941, 1.694, 0.669, 1.107, 0.403], [-1.483, 1.056, 1.615, 0.417, 0.387, 0.739]] C: [[-1.546, -0.182, 1.499, 0.527, 1.029, 0.605], [-1.401, -1.244, 2.308, -0.222, 0.467, 0.206], [-2.193, -1.361, 0.929, 0.133, 0.525, 0.091], [-1.321, 1.865, 1.781, -0.053, 0.666, 0.358], [-1.503, 1.488, 1.689, 0.165, 0.203, 0.17]] D: [[-1.94, -0.345, 2.215, 0.028, 0.642, 0.092], [-2.035, -1.654, 1.937, 0.612, 1.134, -0.102], [-1.249, -1.385, 0.367, 0.613, 1.003, 0.682], [-2.01, 1.507, 1.513, 0.614, 0.573, 0.003], [-1.183, 1.016, 0.985, -0.012, 0.86, 0.417]]
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: [[0.725417, 0.297171, -0.620854], [0.687848, -0.279954, 0.669695], [0.025203, -0.912861, -0.407492]]; the translation vector: [3.434752, 3.057745, 1.556519], 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: [[-1.718, -0.44, 1.96, 0.228, 0.897, 0.293], [-1.706, -1.293, 1.868, 0.22, 0.846, 0.362], [-1.707, -1.314, 0.762, 0.375, 0.826, 0.302], [-1.691, 1.543, 1.626, 0.337, 0.697, 0.437], [-1.573, 1.406, 1.291, 0.181, 0.564, 0.313]] B: [[-1.988, -0.706, 1.585, 0.615, 0.861, 0.547], [-1.403, -1.309, 1.785, -0.129, 1.049, -0.092], [-1.749, -1.25, 0.92, 0.869, 1.088, 0.428], [-1.92, 1.941, 1.694, 0.669, 1.107, 0.403], [-1.483, 1.056, 1.615, 0.417, 0.387, 0.739]] C: [[-1.546, -0.182, 1.499, 0.527, 1.029, 0.605], [-1.401, -1.244, 2.308, -0.222, 0.467, 0.206], [-2.193, -1.361, 0.929, 0.133, 0.525, 0.091], [-1.321, 1.865, 1.781, -0.053, 0.666, 0.358], [-1.503, 1.488, 1.689, 0.165, 0.203, 0.17]] D: [[-1.94, -0.345, 2.215, 0.028, 0.642, 0.092], [-2.035, -1.654, 1.937, 0.612, 1.134, -0.102], [-1.249, -1.385, 0.367, 0.613, 1.003, 0.682], [-2.01, 1.507, 1.513, 0.614, 0.573, 0.003], [-1.183, 1.016, 0.985, -0.012, 0.86, 0.417]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_21_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_21_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.266, 0.688, 1.427, 0.645, 4.144, 1.891], [1.793, 0.377, 0.356, 0.744, 3.81, 1.61], [-0.941, -1.334, 0.579, 2.335, 0.039, 1.673], [0.362, -1.428, 0.335, 0.484, 0.146, 1.101], [0.403, -1.616, 0.92, 1.722, 0.842, 1.057], [1.194, 3.045, 0.588, 0.013, 0.929, 1.121], [1.761, 2.38, 0.509, 0.767, -0.159, 0.975]] B: [[-2.307, 0.099, 1.206, 0.234, 3.804, 1.593], [2.401, 0.098, 0.732, 0.485, 3.642, 1.662], [-1.38, -1.427, 1.26, 2.485, 0.117, 1.419], [0.047, -1.412, 0.542, 0.454, 0.56, 1.109], [0.451, -2.029, 0.885, 1.313, 0.841, 0.961], [1.821, 2.284, 0.965, -0.181, 0.842, 1.118], [1.675, 2.553, 0.956, 0.491, 0.104, 1.591]] C: [[-1.548, 0.69, 1.589, 0.293, 3.816, 1.624], [2.411, 0.459, 0.334, 0.543, 4.513, 1.336], [-0.832, -2.051, 0.999, 1.925, 0.593, 1.075], [-0.217, -1.618, 0.815, -0.295, 0.494, 0.985], [1.068, -1.834, 1.273, 1.646, 0.657, 0.959], [1.898, 2.458, 0.543, 0.44, 1.518, 1.452], [2.071, 1.877, 0.293, 1.12, 0.358, 1.716]] D: [[-1.964, 0.397, 1.135, 0.305, 4.04, 1.813], [2.143, 0.114, 0.673, 0.413, 4.08, 1.439], [-0.926, -1.676, 0.892, 2.284, 0.231, 1.529], [0.195, -1.875, 0.811, 0.153, 0.424, 1.364], [0.78, -1.998, 0.788, 1.226, 0.36, 1.309], [1.439, 2.685, 0.692, 0.249, 1.216, 1.435], [1.802, 2.098, 0.616, 0.629, 0.105, 1.315]]
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: [[0.205292, 0.226186, -0.952205], [0.97316, -0.150555, 0.174048], [-0.103992, -0.962379, -0.251024]]; the translation vector: [4.876985, 2.837537, 1.671042], 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: [[-2.266, 0.688, 1.427, 0.645, 4.144, 1.891], [1.793, 0.377, 0.356, 0.744, 3.81, 1.61], [-0.941, -1.334, 0.579, 2.335, 0.039, 1.673], [0.362, -1.428, 0.335, 0.484, 0.146, 1.101], [0.403, -1.616, 0.92, 1.722, 0.842, 1.057], [1.194, 3.045, 0.588, 0.013, 0.929, 1.121], [1.761, 2.38, 0.509, 0.767, -0.159, 0.975]] B: [[-2.307, 0.099, 1.206, 0.234, 3.804, 1.593], [2.401, 0.098, 0.732, 0.485, 3.642, 1.662], [-1.38, -1.427, 1.26, 2.485, 0.117, 1.419], [0.047, -1.412, 0.542, 0.454, 0.56, 1.109], [0.451, -2.029, 0.885, 1.313, 0.841, 0.961], [1.821, 2.284, 0.965, -0.181, 0.842, 1.118], [1.675, 2.553, 0.956, 0.491, 0.104, 1.591]] C: [[-1.548, 0.69, 1.589, 0.293, 3.816, 1.624], [2.411, 0.459, 0.334, 0.543, 4.513, 1.336], [-0.832, -2.051, 0.999, 1.925, 0.593, 1.075], [-0.217, -1.618, 0.815, -0.295, 0.494, 0.985], [1.068, -1.834, 1.273, 1.646, 0.657, 0.959], [1.898, 2.458, 0.543, 0.44, 1.518, 1.452], [2.071, 1.877, 0.293, 1.12, 0.358, 1.716]] D: [[-1.964, 0.397, 1.135, 0.305, 4.04, 1.813], [2.143, 0.114, 0.673, 0.413, 4.08, 1.439], [-0.926, -1.676, 0.892, 2.284, 0.231, 1.529], [0.195, -1.875, 0.811, 0.153, 0.424, 1.364], [0.78, -1.998, 0.788, 1.226, 0.36, 1.309], [1.439, 2.685, 0.692, 0.249, 1.216, 1.435], [1.802, 2.098, 0.616, 0.629, 0.105, 1.315]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_22_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_22_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.121, -0.501, -0.221, 0.439, 0.387, 0.089], [1.109, -1.077, -0.06, 0.221, 0.081, 0.556]] B: [[-0.019, -0.497, 0.389, 1.016, 0.944, 0.39], [1.279, -1.542, -0.239, 0.195, 0.216, 0.872]] C: [[0.21, -0.049, -0.032, 0.947, 0.552, 0.204], [0.617, -0.987, 0.392, 0.284, 0.553, 0.828]] D: [[0.392, -0.219, 0.176, 0.595, 0.63, 0.481], [0.882, -1.099, 0.197, 0.524, 0.524, 0.466]]
Given a RGB image and a depth image, please detect the 3D bounding box of the ottoman in the scene. The camera pose information includes: the rotation matrix: [[0.133825, -0.39571, 0.908573], [-0.990975, -0.046263, 0.125813], [-0.007752, -0.91721, -0.398329]]; the translation vector: [4.990516, 4.227292, 1.32289], 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: [[0.121, -0.501, -0.221, 0.439, 0.387, 0.089], [1.109, -1.077, -0.06, 0.221, 0.081, 0.556]] B: [[-0.019, -0.497, 0.389, 1.016, 0.944, 0.39], [1.279, -1.542, -0.239, 0.195, 0.216, 0.872]] C: [[0.21, -0.049, -0.032, 0.947, 0.552, 0.204], [0.617, -0.987, 0.392, 0.284, 0.553, 0.828]] D: [[0.392, -0.219, 0.176, 0.595, 0.63, 0.481], [0.882, -1.099, 0.197, 0.524, 0.524, 0.466]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_23_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_23_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.923, 3.072, 1.641, 0.406, 0.224, 0.224], [0.852, 2.684, 1.628, 0.411, 0.369, 0.342], [0.952, 2.353, 1.591, 0.332, 0.315, 0.303], [0.919, 1.934, 1.549, 0.278, 0.356, 0.3], [0.991, 1.596, 1.521, 0.302, 0.285, 0.248], [1.083, 1.197, 1.51, 0.2, 0.428, 0.292], [1.067, 0.874, 1.479, 0.258, 0.387, 0.349], [1.029, 0.682, 1.414, 0.27, 0.238, 0.229], [1.041, 0.446, 1.386, 0.31, 0.355, 0.267], [1.007, 0.119, 1.367, 0.313, 0.297, 0.251], [1.072, -0.152, 1.331, 0.368, 0.301, 0.196], [0.978, -0.542, 1.366, 0.293, 0.411, 0.344], [1.038, -0.846, 1.349, 0.398, 0.352, 0.371], [0.995, -1.285, 1.277, 0.273, 0.319, 0.287], [1.051, -1.623, 1.317, 0.372, 0.433, 0.346], [1.016, -1.909, 1.267, 0.375, 0.379, 0.355], [1.01, -2.206, 1.239, 0.32, 0.305, 0.33], [1.021, -2.389, 1.248, 0.292, 0.375, 0.256], [0.945, -2.669, 1.168, 0.312, 0.307, 0.249], [0.986, -2.904, 1.157, 0.265, 0.331, 0.203]] B: [[1.16, 2.801, 1.566, 0.581, 0.486, -0.268], [0.756, 2.458, 1.347, -0.04, 0.522, 0.189], [0.535, 2.032, 1.866, 0.051, 0.318, 0.012], [0.896, 2.321, 1.823, -0.143, 0.711, 0.696], [1.3, 1.485, 1.216, 0.089, 0.474, 0.726], [1.333, 1.63, 1.281, 0.587, 0.639, -0.131], [1.034, 0.752, 1.496, 0.694, 0.45, 0.002], [1.132, 0.488, 1.903, -0.121, -0.068, 0.586], [1.244, 0.056, 1.06, 0.343, 0.366, 0.492], [0.523, 0.369, 1.091, 0.036, 0.297, 0.341], [0.945, -0.379, 1.231, -0.009, 0.698, 0.282], [0.742, -0.538, 1.804, 0.143, 0.887, 0.377], [1.245, -0.568, 1.71, 0.143, 0.603, 0.41], [1.356, -0.879, 1.397, 0.576, 0.048, 0.554], [1.47, -2.036, 1.112, 0.54, 0.795, 0.096], [1.472, -1.52, 0.829, 0.648, 0.598, 0.49], [0.775, -2.633, 1.506, -0.16, -0.139, -0.099], [0.838, -2.702, 1.211, 0.137, 0.331, -0.011], [1.261, -2.818, 1.474, 0.679, -0.005, 0.352], [0.793, -2.949, 1.566, -0.008, 0.477, 0.693]] C: [[1.056, 2.871, 1.196, 0.82, -0.168, 0.476], [1.086, 3.168, 1.177, -0.05, 0.768, 0.624], [1.078, 2.314, 1.991, 0.481, -0.014, 0.382], [0.899, 1.855, 1.409, -0.073, 0.065, 0.078], [0.796, 1.846, 1.026, -0.008, 0.461, 0.294], [0.96, 0.751, 1.316, 0.52, 0.805, 0.752], [1.18, 1.031, 1.766, 0.673, 0.119, 0.034], [1.398, 0.505, 1.118, -0.168, 0.16, -0.249], [0.838, 0.65, 1.392, 0.173, 0.458, 0.332], [1.111, -0.328, 1.396, 0.558, 0.481, 0.366], [0.597, -0.355, 1.146, 0.623, 0.368, 0.632], [0.691, -0.514, 1.338, -0.157, 0.304, -0.124], [0.696, -1.125, 1.476, 0.501, 0.757, 0.356], [0.907, -0.859, 1.385, 0.656, 0.571, -0.029], [1.035, -1.127, 1.219, 0.093, 0.841, 0.704], [0.635, -1.763, 1.501, -0.076, -0.097, 0.162], [0.614, -1.848, 1.062, 0.328, 0.483, 0.674], [0.692, -2.453, 1.556, 0.665, 0.718, 0.625], [1.074, -2.937, 1.026, 0.776, 0.224, 0.639], [0.852, -3.222, 1.01, 0.571, -0.139, 0.12]] D: [[1.022, 3.318, 1.189, 0.205, -0.146, 0.042], [0.815, 2.622, 1.239, 0.213, 0.653, 0.265], [1.051, 2.623, 1.858, 0.743, -0.174, 0.425], [1.36, 1.47, 1.216, -0.071, -0.098, -0.074], [1.312, 2.017, 2.002, -0.015, 0.439, 0.124], [0.798, 1.663, 1.184, 0.218, 0.773, 0.512], [1.438, 0.663, 1.321, 0.334, 0.497, 0.799], [1.496, 1.067, 1.009, 0.492, 0.69, -0.197], [0.673, 0.916, 1.137, 0.692, -0.115, 0.537], [0.588, 0.319, 1.507, 0.723, 0.486, 0.106], [0.938, -0.596, 1.384, 0.378, 0.487, -0.284], [0.718, -0.867, 0.941, 0.405, 0.388, -0.074], [1.365, -0.417, 1.613, 0.897, 0.508, -0.003], [1.124, -1.228, 1.16, 0.374, 0.651, 0.692], [0.872, -1.666, 1.25, 0.857, 0.612, -0.1], [0.693, -1.777, 1.038, 0.754, 0.733, 0.072], [1.133, -1.714, 1.626, 0.475, -0.192, 0.478], [1.392, -2.804, 1.671, -0.124, 0.18, 0.524], [1.024, -2.671, 1.235, 0.602, 0.29, 0.162], [0.636, -2.621, 1.52, -0.11, 0.64, 0.18]]
Given a RGB image and a depth image, please detect the 3D bounding box of the book in the scene. The camera pose information includes: the rotation matrix: [[0.999403, 0.004498, 0.03425], [-0.034232, -0.004158, 0.999405], [0.004638, -0.999981, -0.004001]]; the translation vector: [2.393484, 5.775056, 1.371464], 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: [[0.923, 3.072, 1.641, 0.406, 0.224, 0.224], [0.852, 2.684, 1.628, 0.411, 0.369, 0.342], [0.952, 2.353, 1.591, 0.332, 0.315, 0.303], [0.919, 1.934, 1.549, 0.278, 0.356, 0.3], [0.991, 1.596, 1.521, 0.302, 0.285, 0.248], [1.083, 1.197, 1.51, 0.2, 0.428, 0.292], [1.067, 0.874, 1.479, 0.258, 0.387, 0.349], [1.029, 0.682, 1.414, 0.27, 0.238, 0.229], [1.041, 0.446, 1.386, 0.31, 0.355, 0.267], [1.007, 0.119, 1.367, 0.313, 0.297, 0.251], [1.072, -0.152, 1.331, 0.368, 0.301, 0.196], [0.978, -0.542, 1.366, 0.293, 0.411, 0.344], [1.038, -0.846, 1.349, 0.398, 0.352, 0.371], [0.995, -1.285, 1.277, 0.273, 0.319, 0.287], [1.051, -1.623, 1.317, 0.372, 0.433, 0.346], [1.016, -1.909, 1.267, 0.375, 0.379, 0.355], [1.01, -2.206, 1.239, 0.32, 0.305, 0.33], [1.021, -2.389, 1.248, 0.292, 0.375, 0.256], [0.945, -2.669, 1.168, 0.312, 0.307, 0.249], [0.986, -2.904, 1.157, 0.265, 0.331, 0.203]] B: [[1.16, 2.801, 1.566, 0.581, 0.486, -0.268], [0.756, 2.458, 1.347, -0.04, 0.522, 0.189], [0.535, 2.032, 1.866, 0.051, 0.318, 0.012], [0.896, 2.321, 1.823, -0.143, 0.711, 0.696], [1.3, 1.485, 1.216, 0.089, 0.474, 0.726], [1.333, 1.63, 1.281, 0.587, 0.639, -0.131], [1.034, 0.752, 1.496, 0.694, 0.45, 0.002], [1.132, 0.488, 1.903, -0.121, -0.068, 0.586], [1.244, 0.056, 1.06, 0.343, 0.366, 0.492], [0.523, 0.369, 1.091, 0.036, 0.297, 0.341], [0.945, -0.379, 1.231, -0.009, 0.698, 0.282], [0.742, -0.538, 1.804, 0.143, 0.887, 0.377], [1.245, -0.568, 1.71, 0.143, 0.603, 0.41], [1.356, -0.879, 1.397, 0.576, 0.048, 0.554], [1.47, -2.036, 1.112, 0.54, 0.795, 0.096], [1.472, -1.52, 0.829, 0.648, 0.598, 0.49], [0.775, -2.633, 1.506, -0.16, -0.139, -0.099], [0.838, -2.702, 1.211, 0.137, 0.331, -0.011], [1.261, -2.818, 1.474, 0.679, -0.005, 0.352], [0.793, -2.949, 1.566, -0.008, 0.477, 0.693]] C: [[1.056, 2.871, 1.196, 0.82, -0.168, 0.476], [1.086, 3.168, 1.177, -0.05, 0.768, 0.624], [1.078, 2.314, 1.991, 0.481, -0.014, 0.382], [0.899, 1.855, 1.409, -0.073, 0.065, 0.078], [0.796, 1.846, 1.026, -0.008, 0.461, 0.294], [0.96, 0.751, 1.316, 0.52, 0.805, 0.752], [1.18, 1.031, 1.766, 0.673, 0.119, 0.034], [1.398, 0.505, 1.118, -0.168, 0.16, -0.249], [0.838, 0.65, 1.392, 0.173, 0.458, 0.332], [1.111, -0.328, 1.396, 0.558, 0.481, 0.366], [0.597, -0.355, 1.146, 0.623, 0.368, 0.632], [0.691, -0.514, 1.338, -0.157, 0.304, -0.124], [0.696, -1.125, 1.476, 0.501, 0.757, 0.356], [0.907, -0.859, 1.385, 0.656, 0.571, -0.029], [1.035, -1.127, 1.219, 0.093, 0.841, 0.704], [0.635, -1.763, 1.501, -0.076, -0.097, 0.162], [0.614, -1.848, 1.062, 0.328, 0.483, 0.674], [0.692, -2.453, 1.556, 0.665, 0.718, 0.625], [1.074, -2.937, 1.026, 0.776, 0.224, 0.639], [0.852, -3.222, 1.01, 0.571, -0.139, 0.12]] D: [[1.022, 3.318, 1.189, 0.205, -0.146, 0.042], [0.815, 2.622, 1.239, 0.213, 0.653, 0.265], [1.051, 2.623, 1.858, 0.743, -0.174, 0.425], [1.36, 1.47, 1.216, -0.071, -0.098, -0.074], [1.312, 2.017, 2.002, -0.015, 0.439, 0.124], [0.798, 1.663, 1.184, 0.218, 0.773, 0.512], [1.438, 0.663, 1.321, 0.334, 0.497, 0.799], [1.496, 1.067, 1.009, 0.492, 0.69, -0.197], [0.673, 0.916, 1.137, 0.692, -0.115, 0.537], [0.588, 0.319, 1.507, 0.723, 0.486, 0.106], [0.938, -0.596, 1.384, 0.378, 0.487, -0.284], [0.718, -0.867, 0.941, 0.405, 0.388, -0.074], [1.365, -0.417, 1.613, 0.897, 0.508, -0.003], [1.124, -1.228, 1.16, 0.374, 0.651, 0.692], [0.872, -1.666, 1.25, 0.857, 0.612, -0.1], [0.693, -1.777, 1.038, 0.754, 0.733, 0.072], [1.133, -1.714, 1.626, 0.475, -0.192, 0.478], [1.392, -2.804, 1.671, -0.124, 0.18, 0.524], [1.024, -2.671, 1.235, 0.602, 0.29, 0.162], [0.636, -2.621, 1.52, -0.11, 0.64, 0.18]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_24_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_24_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.127, 1.263, 0.842, 1.099, 0.165, 0.151], [0.899, 0.349, 0.833, 0.078, 0.633, 0.087]] B: [[-0.285, 1.099, 0.515, 1.523, 0.256, -0.319], [0.56, 0.838, 0.875, -0.327, 0.985, 0.228]] C: [[0.446, 1.442, 1.259, 1.427, 0.331, 0.006], [0.446, 0.556, 0.643, 0.276, 0.563, -0.341]] D: [[-0.356, 1.631, 0.612, 0.864, 0.511, -0.226], [0.523, 0.674, 0.57, 0.567, 0.594, 0.019]]
Given a RGB image and a depth image, please detect the 3D bounding box of the rail in the scene. The camera pose information includes: the rotation matrix: [[0.631332, 0.312126, -0.709927], [0.775472, -0.26347, 0.573784], [-0.007951, -0.912776, -0.408382]]; the translation vector: [1.600176, 0.624978, 1.327739], 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: [[0.127, 1.263, 0.842, 1.099, 0.165, 0.151], [0.899, 0.349, 0.833, 0.078, 0.633, 0.087]] B: [[-0.285, 1.099, 0.515, 1.523, 0.256, -0.319], [0.56, 0.838, 0.875, -0.327, 0.985, 0.228]] C: [[0.446, 1.442, 1.259, 1.427, 0.331, 0.006], [0.446, 0.556, 0.643, 0.276, 0.563, -0.341]] D: [[-0.356, 1.631, 0.612, 0.864, 0.511, -0.226], [0.523, 0.674, 0.57, 0.567, 0.594, 0.019]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_25_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_25_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.787, 2.876, 1.457, 2.063, -0.079, 1.518], [-0.953, 1.998, 0.997, 0.069, 3.579, 2.369], [0.693, -0.876, 1.265, 0.33, 4.219, 2.072], [0.345, -2.632, 0.88, 1.928, -0.067, 1.565], [-0.455, -2.068, 1.068, 0.08, 1.617, 2.382], [-0.899, -1.196, 0.623, 0.651, 0.095, 2.066]] B: [[0.116, 3.687, 0.955, 2.711, 0.51, 1.785], [-0.801, 1.888, 0.628, 0.573, 3.732, 2.205], [1.093, -0.187, 0.521, -0.148, 5.045, 2.538], [0.42, -2.481, 1.79, 1.307, 0.36, 0.947], [-0.514, -1.855, 0.567, 0.468, 1.76, 1.511], [-1.181, -1.155, 0.753, 0.267, -0.268, 1.847]] C: [[0.302, 3.207, 1.219, 2.255, 0.306, 1.414], [-0.871, 1.59, 0.966, 0.239, 3.492, 2.066], [0.732, -0.454, 0.961, 0.242, 4.576, 2.069], [-0.078, -2.664, 1.355, 1.624, 0.192, 1.303], [-0.886, -1.849, 0.913, 0.175, 1.703, 1.972], [-1.091, -1.016, 0.816, 0.518, 0.228, 1.826]] D: [[0.349, 2.764, 1.178, 2.112, -0.17, 1.603], [-1.032, 1.356, 0.914, 0.415, 3.877, 2.097], [0.285, -0.798, 1.205, 0.303, 4.409, 2.223], [-0.233, -2.574, 1.577, 1.241, 0.359, 1.513], [-1.059, -2.05, 1.259, 0.503, 1.807, 1.753], [-1.108, -1.393, 0.584, 0.052, -0.001, 1.469]]
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: [[-0.386761, -0.304254, 0.870543], [-0.920043, 0.191539, -0.34181], [-0.062746, -0.933136, -0.354007]]; the translation vector: [2.082368, 4.008438, 1.845888], 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: [[0.787, 2.876, 1.457, 2.063, -0.079, 1.518], [-0.953, 1.998, 0.997, 0.069, 3.579, 2.369], [0.693, -0.876, 1.265, 0.33, 4.219, 2.072], [0.345, -2.632, 0.88, 1.928, -0.067, 1.565], [-0.455, -2.068, 1.068, 0.08, 1.617, 2.382], [-0.899, -1.196, 0.623, 0.651, 0.095, 2.066]] B: [[0.116, 3.687, 0.955, 2.711, 0.51, 1.785], [-0.801, 1.888, 0.628, 0.573, 3.732, 2.205], [1.093, -0.187, 0.521, -0.148, 5.045, 2.538], [0.42, -2.481, 1.79, 1.307, 0.36, 0.947], [-0.514, -1.855, 0.567, 0.468, 1.76, 1.511], [-1.181, -1.155, 0.753, 0.267, -0.268, 1.847]] C: [[0.302, 3.207, 1.219, 2.255, 0.306, 1.414], [-0.871, 1.59, 0.966, 0.239, 3.492, 2.066], [0.732, -0.454, 0.961, 0.242, 4.576, 2.069], [-0.078, -2.664, 1.355, 1.624, 0.192, 1.303], [-0.886, -1.849, 0.913, 0.175, 1.703, 1.972], [-1.091, -1.016, 0.816, 0.518, 0.228, 1.826]] D: [[0.349, 2.764, 1.178, 2.112, -0.17, 1.603], [-1.032, 1.356, 0.914, 0.415, 3.877, 2.097], [0.285, -0.798, 1.205, 0.303, 4.409, 2.223], [-0.233, -2.574, 1.577, 1.241, 0.359, 1.513], [-1.059, -2.05, 1.259, 0.503, 1.807, 1.753], [-1.108, -1.393, 0.584, 0.052, -0.001, 1.469]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_26_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_26_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.506, 0.209, 0.255, 0.924, 1.928, 0.478], [0.463, -1.087, 0.626, 1.179, 0.62, 0.996], [2.049, 0.799, -0.061, 0.618, 1.041, 1.191]] B: [[-2.054, 0.6, 0.688, 1.044, 1.508, 0.567], [0.964, -1.042, 0.495, 1.122, 0.573, 0.421], [2.453, 0.513, 0.739, 0.463, 1.578, 0.424]] C: [[-2.686, -0.003, 0.374, 0.562, 1.486, 0.489], [1.084, -0.733, 0.31, 1.073, 1.131, 0.967], [1.7, 0.788, 0.091, 0.433, 1.461, 1.21]] D: [[-2.225, 0.184, 0.565, 0.652, 1.867, 0.966], [0.89, -0.986, 0.428, 1.537, 0.782, 0.844], [2.106, 0.485, 0.423, 0.73, 1.476, 0.84]]
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: [[-0.565317, -0.50256, 0.654103], [-0.824719, 0.328974, -0.460017], [0.016003, -0.799506, -0.600445]]; the translation vector: [4.07549, 5.065369, 1.281872], 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: [[-2.506, 0.209, 0.255, 0.924, 1.928, 0.478], [0.463, -1.087, 0.626, 1.179, 0.62, 0.996], [2.049, 0.799, -0.061, 0.618, 1.041, 1.191]] B: [[-2.054, 0.6, 0.688, 1.044, 1.508, 0.567], [0.964, -1.042, 0.495, 1.122, 0.573, 0.421], [2.453, 0.513, 0.739, 0.463, 1.578, 0.424]] C: [[-2.686, -0.003, 0.374, 0.562, 1.486, 0.489], [1.084, -0.733, 0.31, 1.073, 1.131, 0.967], [1.7, 0.788, 0.091, 0.433, 1.461, 1.21]] D: [[-2.225, 0.184, 0.565, 0.652, 1.867, 0.966], [0.89, -0.986, 0.428, 1.537, 0.782, 0.844], [2.106, 0.485, 0.423, 0.73, 1.476, 0.84]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_27_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_27_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.787, -0.535, 0.927, 0.017, -0.194, -0.206]] B: [[-1.049, -0.444, 0.739, 0.127, 0.097, 0.179]] C: [[-1.148, -0.307, 0.649, -0.194, 0.004, 0.501]] D: [[-1.423, -0.784, 0.923, 0.285, 0.539, 0.33]]
Given a RGB image and a depth image, please detect the 3D bounding box of the water bottle in the scene. The camera pose information includes: the rotation matrix: [[0.684823, -0.326379, 0.651532], [-0.728707, -0.304485, 0.613413], [-0.001823, -0.894855, -0.446353]]; the translation vector: [2.86358, 2.414664, 1.549631], 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: [[-0.787, -0.535, 0.927, 0.017, -0.194, -0.206]] B: [[-1.049, -0.444, 0.739, 0.127, 0.097, 0.179]] C: [[-1.148, -0.307, 0.649, -0.194, 0.004, 0.501]] D: [[-1.423, -0.784, 0.923, 0.285, 0.539, 0.33]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_28_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_28_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.125, -0.371, 0.52, 0.921, 0.949, 1.032], [-0.05, 0.47, 0.51, 0.929, 1.055, 1.018]] B: [[-0.03, 0.021, 0.629, 1.294, 0.744, 0.853], [0.141, 0.523, 0.057, 0.461, 0.601, 1.102]] C: [[-0.027, -0.543, 0.255, 1.392, 0.459, 1.351], [-0.542, 0.241, 0.854, 1.099, 1.281, 1.01]] D: [[-0.353, -0.617, 0.621, 0.568, 1.229, 1.321], [-0.327, 0.58, 0.56, 0.835, 0.644, 0.683]]
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: [[0.935902, 0.160482, -0.313582], [0.351212, -0.493772, 0.795512], [-0.027173, -0.854655, -0.518485]]; the translation vector: [4.465, -0.226232, 1.550028], 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: [[-0.125, -0.371, 0.52, 0.921, 0.949, 1.032], [-0.05, 0.47, 0.51, 0.929, 1.055, 1.018]] B: [[-0.03, 0.021, 0.629, 1.294, 0.744, 0.853], [0.141, 0.523, 0.057, 0.461, 0.601, 1.102]] C: [[-0.027, -0.543, 0.255, 1.392, 0.459, 1.351], [-0.542, 0.241, 0.854, 1.099, 1.281, 1.01]] D: [[-0.353, -0.617, 0.621, 0.568, 1.229, 1.321], [-0.327, 0.58, 0.56, 0.835, 0.644, 0.683]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_29_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_29_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.113, 1.152, 0.299, 1.212, 0.824, 1.479], [-0.739, -1.761, 0.838, 1.759, 0.908, 0.436]] B: [[-1.686, 0.962, 0.402, 1.418, 0.984, 0.915], [-0.524, -1.303, 0.377, 1.429, 0.342, 0.995]] C: [[-1.37, 1.148, 0.616, 1.114, 0.537, 1.159], [-0.283, -1.543, 0.412, 1.531, 0.506, 0.887]] D: [[-1.358, 1.603, 0.665, 1.495, 0.045, 1.488], [0.077, -1.171, 0.113, 1.245, 0.683, 1.338]]
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: [[0.993306, 0.029023, -0.111812], [0.110831, -0.512349, 0.851596], [-0.032571, -0.858287, -0.512136]]; the translation vector: [2.482234, 1.391135, 1.348064], 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: [[-1.113, 1.152, 0.299, 1.212, 0.824, 1.479], [-0.739, -1.761, 0.838, 1.759, 0.908, 0.436]] B: [[-1.686, 0.962, 0.402, 1.418, 0.984, 0.915], [-0.524, -1.303, 0.377, 1.429, 0.342, 0.995]] C: [[-1.37, 1.148, 0.616, 1.114, 0.537, 1.159], [-0.283, -1.543, 0.412, 1.531, 0.506, 0.887]] D: [[-1.358, 1.603, 0.665, 1.495, 0.045, 1.488], [0.077, -1.171, 0.113, 1.245, 0.683, 1.338]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_30_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_30_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.429, 0.564, 1.259, 0.514, 4.432, 2.586], [-1.998, 0.309, 1.385, 0.292, 3.896, 2.792], [0.693, 2.704, 1.079, 1.949, 0.124, 2.2]] B: [[1.111, 0.098, 1.082, 0.466, 4.575, 2.917], [-1.93, 0.083, 1.425, -0.025, 4.078, 2.389], [0.372, 3.074, 1.309, 1.613, 0.349, 2.653]] C: [[1.746, 0.141, 1.259, 0.14, 4.199, 2.418], [-1.8, 0.062, 1.744, -0.163, 3.558, 2.447], [0.931, 3.17, 1.18, 1.489, -0.095, 2.336]] D: [[1.116, 0.433, 1.412, 0.515, 4.324, 2.69], [-1.509, 0.174, 1.744, -0.053, 3.532, 2.532], [0.744, 2.248, 0.965, 1.964, 0.231, 1.764]]
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: [[-0.32152, -0.4706, 0.821681], [-0.946681, 0.178549, -0.268172], [-0.020508, -0.864092, -0.502915]]; the translation vector: [2.120097, 2.367636, 1.494245], 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: [[1.429, 0.564, 1.259, 0.514, 4.432, 2.586], [-1.998, 0.309, 1.385, 0.292, 3.896, 2.792], [0.693, 2.704, 1.079, 1.949, 0.124, 2.2]] B: [[1.111, 0.098, 1.082, 0.466, 4.575, 2.917], [-1.93, 0.083, 1.425, -0.025, 4.078, 2.389], [0.372, 3.074, 1.309, 1.613, 0.349, 2.653]] C: [[1.746, 0.141, 1.259, 0.14, 4.199, 2.418], [-1.8, 0.062, 1.744, -0.163, 3.558, 2.447], [0.931, 3.17, 1.18, 1.489, -0.095, 2.336]] D: [[1.116, 0.433, 1.412, 0.515, 4.324, 2.69], [-1.509, 0.174, 1.744, -0.053, 3.532, 2.532], [0.744, 2.248, 0.965, 1.964, 0.231, 1.764]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_31_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_31_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.189, -0.394, 0.453, 1.615, 0.833, 0.943]] B: [[-0.04, -0.278, 0.23, 1.326, 1.046, 0.463]] C: [[-0.492, -0.1, 0.679, 1.535, 0.67, -0.014]] D: [[0.006, 0.067, 0.535, 1.038, 1.473, 0.446]]
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: [[-0.799511, 0.533863, -0.275266], [0.600541, 0.71925, -0.349328], [0.011492, -0.4446, -0.895656]]; the translation vector: [2.031323, 2.312379, 1.200993], 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: [[0.189, -0.394, 0.453, 1.615, 0.833, 0.943]] B: [[-0.04, -0.278, 0.23, 1.326, 1.046, 0.463]] C: [[-0.492, -0.1, 0.679, 1.535, 0.67, -0.014]] D: [[0.006, 0.067, 0.535, 1.038, 1.473, 0.446]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_32_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_32_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.534, -3.167, 1.655, 0.929, 0.443, 2.126]] B: [[1.524, -3.177, 0.91, 0.507, 0.601, 2.272]] C: [[1.265, -3.361, 1.281, 0.587, 0.91, 2.343]] D: [[1.106, -3.397, 1.033, 0.365, 0.531, 2.023]]
Given a RGB image and a depth image, please detect the 3D bounding box of the shower walls in the scene. The camera pose information includes: the rotation matrix: [[0.590232, -0.352789, 0.726062], [-0.807221, -0.252962, 0.533296], [-0.004475, -0.900861, -0.434086]]; the translation vector: [2.518124, 2.463328, 1.346668], 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: [[1.534, -3.167, 1.655, 0.929, 0.443, 2.126]] B: [[1.524, -3.177, 0.91, 0.507, 0.601, 2.272]] C: [[1.265, -3.361, 1.281, 0.587, 0.91, 2.343]] D: [[1.106, -3.397, 1.033, 0.365, 0.531, 2.023]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_33_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_33_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.432, -0.058, 1.349, -0.208, 0.669, 1.766], [0.527, -0.253, 0.616, -0.259, 1.051, 2.58]] B: [[-1.145, -0.538, 0.911, 0.071, 0.71, 1.954], [0.803, -0.422, 1.032, 0.108, 0.84, 2.211]] C: [[-1.363, -0.409, 0.647, 0.052, 0.929, 2.359], [0.332, 0.057, 1.462, -0.091, 0.807, 2.526]] D: [[-1.139, -0.369, 0.72, -0.007, 0.535, 2.292], [0.44, -0.22, 1.3, 0.54, 1.144, 2.107]]
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: [[-0.464707, 0.496079, -0.733453], [0.882598, 0.326106, -0.338639], [0.071191, -0.804711, -0.589382]]; the translation vector: [2.864701, 0.868861, 1.204561], 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: [[-1.432, -0.058, 1.349, -0.208, 0.669, 1.766], [0.527, -0.253, 0.616, -0.259, 1.051, 2.58]] B: [[-1.145, -0.538, 0.911, 0.071, 0.71, 1.954], [0.803, -0.422, 1.032, 0.108, 0.84, 2.211]] C: [[-1.363, -0.409, 0.647, 0.052, 0.929, 2.359], [0.332, 0.057, 1.462, -0.091, 0.807, 2.526]] D: [[-1.139, -0.369, 0.72, -0.007, 0.535, 2.292], [0.44, -0.22, 1.3, 0.54, 1.144, 2.107]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_34_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_34_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.366, -0.589, 0.493, 0.271, 1.157, 0.396]] B: [[-2.148, -0.107, 0.643, 0.495, 1.354, 0.165]] C: [[-2.396, -0.378, 0.719, 0.293, 1.134, 0.807]] D: [[-2.162, -0.271, 0.293, -0.116, 0.802, 0.089]]
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: [[0.467192, 0.317292, -0.825262], [0.883302, -0.126478, 0.451421], [0.038855, -0.939856, -0.339354]]; the translation vector: [2.723032, 3.168159, 1.438168], 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: [[-2.366, -0.589, 0.493, 0.271, 1.157, 0.396]] B: [[-2.148, -0.107, 0.643, 0.495, 1.354, 0.165]] C: [[-2.396, -0.378, 0.719, 0.293, 1.134, 0.807]] D: [[-2.162, -0.271, 0.293, -0.116, 0.802, 0.089]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_35_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_35_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.721, -0.518, 0.621, 0.489, 0.194, 0.671], [0.219, 1.2, 0.605, 0.561, 1.11, 0.032]] B: [[1.127, -0.237, 0.575, 0.571, 0.442, 0.463], [0.315, 0.86, 0.589, 0.436, 0.639, 0.436]] C: [[1.534, -0.019, 0.554, 1.064, 0.929, 0.813], [0.238, 0.541, 0.519, 0.085, 0.619, 0.329]] D: [[0.67, 0.235, 1.051, 0.639, -0.039, 0.084], [0.187, 0.38, 0.829, 0.452, 0.327, 0.898]]
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: [[0.473704, -0.275929, 0.836342], [-0.879436, -0.198746, 0.432542], [0.046868, -0.940406, -0.336809]]; the translation vector: [2.984934, 2.048073, 1.446683], 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: [[0.721, -0.518, 0.621, 0.489, 0.194, 0.671], [0.219, 1.2, 0.605, 0.561, 1.11, 0.032]] B: [[1.127, -0.237, 0.575, 0.571, 0.442, 0.463], [0.315, 0.86, 0.589, 0.436, 0.639, 0.436]] C: [[1.534, -0.019, 0.554, 1.064, 0.929, 0.813], [0.238, 0.541, 0.519, 0.085, 0.619, 0.329]] D: [[0.67, 0.235, 1.051, 0.639, -0.039, 0.084], [0.187, 0.38, 0.829, 0.452, 0.327, 0.898]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_36_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_36_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.092, -0.678, 1.584, -0.059, 1.814, 1.264], [-1.925, -0.058, 1.478, -0.34, 2.948, 1.581]] B: [[1.208, -0.318, 1.322, 0.047, 1.935, 1.314], [-2.088, -0.879, 1.441, 0.235, 2.296, 1.085]] C: [[1.41, -0.38, 1.574, 0.141, 1.666, 1.41], [-1.712, -0.407, 1.364, 0.152, 2.69, 1.496]] D: [[1.415, -0.841, 1.953, -0.188, 1.625, 1.182], [-1.333, -0.183, 1.414, 0.172, 2.326, 1.539]]
Given a RGB image and a depth image, please detect the 3D bounding box of the blackboard in the scene. The camera pose information includes: the rotation matrix: [[0.24604, -0.551346, 0.797171], [-0.968826, -0.115295, 0.219278], [-0.028988, -0.826271, -0.562526]]; the translation vector: [1.704247, 2.057158, 1.361636], 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: [[1.092, -0.678, 1.584, -0.059, 1.814, 1.264], [-1.925, -0.058, 1.478, -0.34, 2.948, 1.581]] B: [[1.208, -0.318, 1.322, 0.047, 1.935, 1.314], [-2.088, -0.879, 1.441, 0.235, 2.296, 1.085]] C: [[1.41, -0.38, 1.574, 0.141, 1.666, 1.41], [-1.712, -0.407, 1.364, 0.152, 2.69, 1.496]] D: [[1.415, -0.841, 1.953, -0.188, 1.625, 1.182], [-1.333, -0.183, 1.414, 0.172, 2.326, 1.539]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_37_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_37_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.294, -3.518, 1.054, 3.936, 0.361, 0.915], [0.879, 3.786, 1.41, 2.097, 0.63, 1.328]] B: [[-0.76, -3.309, 1.31, 3.985, 0.372, 1.047], [0.904, 3.311, 1.519, 1.8, 0.243, 1.41]] C: [[-0.969, -3.07, 1.797, 3.572, 0.172, 1.293], [1.021, 3.539, 1.127, 2.014, -0.169, 1.491]] D: [[-0.614, -3.4, 1.295, 4.114, 0.42, 0.553], [0.711, 2.902, 1.12, 1.656, 0.643, 1.016]]
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: [[-0.852441, 0.228219, -0.470383], [0.522431, 0.337001, -0.78326], [-0.020235, -0.913426, -0.406502]]; the translation vector: [1.798405, 5.320803, 1.619482], 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: [[-0.294, -3.518, 1.054, 3.936, 0.361, 0.915], [0.879, 3.786, 1.41, 2.097, 0.63, 1.328]] B: [[-0.76, -3.309, 1.31, 3.985, 0.372, 1.047], [0.904, 3.311, 1.519, 1.8, 0.243, 1.41]] C: [[-0.969, -3.07, 1.797, 3.572, 0.172, 1.293], [1.021, 3.539, 1.127, 2.014, -0.169, 1.491]] D: [[-0.614, -3.4, 1.295, 4.114, 0.42, 0.553], [0.711, 2.902, 1.12, 1.656, 0.643, 1.016]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_38_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_38_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.694, -2.027, 0.441, 1.326, 1.107, 0.898], [-0.288, -2.078, 0.474, 1.039, 1.539, 0.924]] B: [[1.654, -2.115, 0.692, 1.098, 1.029, 0.654], [-0.011, -1.968, 0.288, 1.388, 1.994, 1.185]] C: [[2.035, -2.378, 0.613, 1.604, 1.492, 1.161], [-0.68, -1.93, 0.48, 0.656, 1.897, 0.701]] D: [[1.361, -2.093, 0.306, 1.061, 0.846, 0.974], [-0.065, -1.942, 0.682, 1.519, 1.648, 1.035]]
Given a RGB image and a depth image, please detect the 3D bounding box of the foosball table in the scene. The camera pose information includes: the rotation matrix: [[-0.699126, -0.324611, 0.637064], [-0.713802, 0.265353, -0.648131], [0.041344, -0.907863, -0.417224]]; the translation vector: [0.050403, 3.78209, 1.506908], 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: [[1.694, -2.027, 0.441, 1.326, 1.107, 0.898], [-0.288, -2.078, 0.474, 1.039, 1.539, 0.924]] B: [[1.654, -2.115, 0.692, 1.098, 1.029, 0.654], [-0.011, -1.968, 0.288, 1.388, 1.994, 1.185]] C: [[2.035, -2.378, 0.613, 1.604, 1.492, 1.161], [-0.68, -1.93, 0.48, 0.656, 1.897, 0.701]] D: [[1.361, -2.093, 0.306, 1.061, 0.846, 0.974], [-0.065, -1.942, 0.682, 1.519, 1.648, 1.035]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_39_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_39_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.934, -0.844, -0.178, -0.06, 0.379, 0.377]] B: [[-2.118, -0.866, 0.424, -0.166, 0.218, 0.556]] C: [[-2.075, -0.928, -0.19, 0.558, 0.471, 0.431]] D: [[-1.78, -0.879, 0.057, 0.14, 0.194, 0.118]]
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: [[-0.079918, -0.690871, 0.718547], [-0.996802, 0.055321, -0.057677], [9.6e-05, -0.720858, -0.693082]]; the translation vector: [1.142658, 0.968078, 1.385987], 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: [[-1.934, -0.844, -0.178, -0.06, 0.379, 0.377]] B: [[-2.118, -0.866, 0.424, -0.166, 0.218, 0.556]] C: [[-2.075, -0.928, -0.19, 0.558, 0.471, 0.431]] D: [[-1.78, -0.879, 0.057, 0.14, 0.194, 0.118]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_40_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_40_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.004, -0.056, 0.156, 0.548, 2.574, 0.973], [0.863, 1.538, 0.8, 1.622, 0.932, 0.511]] B: [[-0.752, -0.451, 0.479, 0.974, 2.169, 0.971], [0.505, 1.322, 0.592, 1.774, 0.902, 0.995]] C: [[-0.502, -0.659, 0.53, 0.847, 2.257, 0.624], [0.069, 1.171, 0.213, 2.015, 1.277, 1.24]] D: [[-0.413, -0.371, 0.765, 1.102, 2.094, 1.312], [0.364, 1.532, 0.25, 2.233, 1.243, 0.916]]
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: [[-0.861262, 0.35211, -0.366398], [0.508128, 0.60504, -0.61297], [0.005853, -0.714105, -0.700014]]; the translation vector: [3.145762, 3.637784, 1.437024], 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: [[-1.004, -0.056, 0.156, 0.548, 2.574, 0.973], [0.863, 1.538, 0.8, 1.622, 0.932, 0.511]] B: [[-0.752, -0.451, 0.479, 0.974, 2.169, 0.971], [0.505, 1.322, 0.592, 1.774, 0.902, 0.995]] C: [[-0.502, -0.659, 0.53, 0.847, 2.257, 0.624], [0.069, 1.171, 0.213, 2.015, 1.277, 1.24]] D: [[-0.413, -0.371, 0.765, 1.102, 2.094, 1.312], [0.364, 1.532, 0.25, 2.233, 1.243, 0.916]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_41_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_41_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.464, -1.008, 0.704, 0.548, 0.603, 1.02], [-0.19, -0.382, 0.144, 0.733, 0.716, 0.646], [-0.404, 0.288, 0.436, 0.98, 0.357, 1.05], [1.664, -1.226, -0.006, 0.561, 0.79, 0.588], [0.842, 1.15, 0.487, 0.536, 0.705, 0.632], [0.433, 0.35, -0.074, 0.642, 0.688, 0.335], [1.494, 3.097, 0.552, 0.862, 0.855, 0.649], [-1.799, -1.668, 0.843, 1.135, 1.012, 0.533], [2.071, -0.103, 0.082, 0.7, 0.467, 1.183], [2.558, 1.11, 0.748, 0.486, 0.458, 0.736], [-0.954, 2.892, -0.06, 0.296, 0.278, 1.194], [-1.303, 2.083, 0.061, 0.236, 0.278, 0.444], [-1.569, 0.894, 0.218, 0.482, 1.049, 0.471]] B: [[0.772, -0.719, 0.389, 0.713, 0.789, 0.818], [-0.024, -0.745, 0.397, 0.693, 0.69, 0.791], [-0.445, -0.009, 0.396, 0.704, 0.6, 0.798], [1.881, -0.924, 0.405, 0.629, 0.643, 0.773], [0.681, 0.918, 0.401, 0.691, 0.741, 0.776], [0.646, 0.122, 0.392, 0.618, 0.697, 0.804], [1.675, 2.694, 0.343, 0.794, 0.824, 0.712], [-1.741, -1.918, 0.384, 0.689, 0.734, 0.793], [1.972, 0.182, 0.329, 0.798, 0.905, 0.759], [2.104, 1.432, 0.601, 0.176, 0.467, 0.305], [-1.26, 2.803, 0.397, 0.519, 0.618, 0.85], [-1.699, 1.837, 0.379, 0.732, 0.671, 0.798], [-1.685, 1.314, 0.409, 0.719, 0.764, 0.815]] C: [[0.533, -0.974, 0.234, 0.918, 0.378, 0.964], [-0.355, -1.19, 0.156, 0.302, 0.635, 0.774], [-0.597, 0.157, 0.288, 1.05, 0.184, 0.298], [2.072, -0.909, 0.536, 0.468, 0.691, 0.463], [0.786, 1.284, 0.692, 1.11, 1.012, 1.207], [0.407, 0.333, 0.418, 0.195, 0.858, 0.97], [1.968, 3.191, -0.153, 0.695, 1.269, 0.454], [-1.257, -1.997, 0.349, 0.303, 0.286, 0.552], [2.317, 0.459, 0.175, 0.403, 1.116, 1.213], [2.141, 1.823, 0.68, -0.29, 0.059, -0.035], [-1.354, 3.299, 0.362, 0.406, 0.802, 0.98], [-2.092, 2.265, 0.732, 1.224, 0.725, 0.93], [-1.784, 1.414, 0.713, 0.316, 1.116, 0.675]] D: [[0.989, -0.333, 0.223, 0.813, 0.656, 0.519], [0.19, -0.985, 0.389, 0.303, 0.729, 1.121], [-0.625, 0.156, 0.665, 1.074, 0.926, 0.429], [2.366, -0.669, 0.862, 0.551, 0.718, 0.409], [1.078, 0.548, 0.472, 1.129, 0.587, 0.295], [0.268, -0.298, 0.199, 0.384, 0.582, 0.724], [1.775, 3.124, 0.353, 0.87, 1.306, 0.424], [-2.119, -2.015, 0.712, 0.444, 0.613, 1.097], [2.125, 0.536, -0.025, 0.783, 0.67, 0.385], [2.16, 1.441, 0.464, 0.575, 0.443, 0.108], [-1.127, 3.006, 0.402, 0.226, 0.819, 0.552], [-1.981, 2.007, -0.054, 1.127, 0.372, 0.846], [-1.217, 1.009, -0.072, 0.967, 0.351, 1.126]]
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: [[0.951558, 0.16536, -0.259218], [0.307283, -0.481983, 0.820531], [0.010744, -0.860436, -0.509446]]; the translation vector: [2.919862, 3.428013, 1.521081], 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: [[0.464, -1.008, 0.704, 0.548, 0.603, 1.02], [-0.19, -0.382, 0.144, 0.733, 0.716, 0.646], [-0.404, 0.288, 0.436, 0.98, 0.357, 1.05], [1.664, -1.226, -0.006, 0.561, 0.79, 0.588], [0.842, 1.15, 0.487, 0.536, 0.705, 0.632], [0.433, 0.35, -0.074, 0.642, 0.688, 0.335], [1.494, 3.097, 0.552, 0.862, 0.855, 0.649], [-1.799, -1.668, 0.843, 1.135, 1.012, 0.533], [2.071, -0.103, 0.082, 0.7, 0.467, 1.183], [2.558, 1.11, 0.748, 0.486, 0.458, 0.736], [-0.954, 2.892, -0.06, 0.296, 0.278, 1.194], [-1.303, 2.083, 0.061, 0.236, 0.278, 0.444], [-1.569, 0.894, 0.218, 0.482, 1.049, 0.471]] B: [[0.772, -0.719, 0.389, 0.713, 0.789, 0.818], [-0.024, -0.745, 0.397, 0.693, 0.69, 0.791], [-0.445, -0.009, 0.396, 0.704, 0.6, 0.798], [1.881, -0.924, 0.405, 0.629, 0.643, 0.773], [0.681, 0.918, 0.401, 0.691, 0.741, 0.776], [0.646, 0.122, 0.392, 0.618, 0.697, 0.804], [1.675, 2.694, 0.343, 0.794, 0.824, 0.712], [-1.741, -1.918, 0.384, 0.689, 0.734, 0.793], [1.972, 0.182, 0.329, 0.798, 0.905, 0.759], [2.104, 1.432, 0.601, 0.176, 0.467, 0.305], [-1.26, 2.803, 0.397, 0.519, 0.618, 0.85], [-1.699, 1.837, 0.379, 0.732, 0.671, 0.798], [-1.685, 1.314, 0.409, 0.719, 0.764, 0.815]] C: [[0.533, -0.974, 0.234, 0.918, 0.378, 0.964], [-0.355, -1.19, 0.156, 0.302, 0.635, 0.774], [-0.597, 0.157, 0.288, 1.05, 0.184, 0.298], [2.072, -0.909, 0.536, 0.468, 0.691, 0.463], [0.786, 1.284, 0.692, 1.11, 1.012, 1.207], [0.407, 0.333, 0.418, 0.195, 0.858, 0.97], [1.968, 3.191, -0.153, 0.695, 1.269, 0.454], [-1.257, -1.997, 0.349, 0.303, 0.286, 0.552], [2.317, 0.459, 0.175, 0.403, 1.116, 1.213], [2.141, 1.823, 0.68, -0.29, 0.059, -0.035], [-1.354, 3.299, 0.362, 0.406, 0.802, 0.98], [-2.092, 2.265, 0.732, 1.224, 0.725, 0.93], [-1.784, 1.414, 0.713, 0.316, 1.116, 0.675]] D: [[0.989, -0.333, 0.223, 0.813, 0.656, 0.519], [0.19, -0.985, 0.389, 0.303, 0.729, 1.121], [-0.625, 0.156, 0.665, 1.074, 0.926, 0.429], [2.366, -0.669, 0.862, 0.551, 0.718, 0.409], [1.078, 0.548, 0.472, 1.129, 0.587, 0.295], [0.268, -0.298, 0.199, 0.384, 0.582, 0.724], [1.775, 3.124, 0.353, 0.87, 1.306, 0.424], [-2.119, -2.015, 0.712, 0.444, 0.613, 1.097], [2.125, 0.536, -0.025, 0.783, 0.67, 0.385], [2.16, 1.441, 0.464, 0.575, 0.443, 0.108], [-1.127, 3.006, 0.402, 0.226, 0.819, 0.552], [-1.981, 2.007, -0.054, 1.127, 0.372, 0.846], [-1.217, 1.009, -0.072, 0.967, 0.351, 1.126]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_42_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_42_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.467, 4.66, 0.479, 1.188, 0.953, 0.41], [-0.153, 2.813, 0.487, 0.892, 1.061, 0.54], [0.179, 1.102, 0.898, 0.937, 1.029, 0.418], [1.771, 1.676, 0.076, 1.486, 0.58, 0.338], [1.933, -1.484, -0.005, 1.579, 0.28, 0.413], [-0.13, 5.403, 0.908, 0.195, 1.153, 0.536]] B: [[2.334, 4.242, 0.72, 1.63, 0.144, 0.491], [-0.388, 2.622, 0.373, 0.028, 1.059, 0.86], [0.405, 0.837, 0.295, 0.037, 1.048, 0.862], [2.233, 1.663, 0.713, 1.024, 0.482, 0.49], [1.733, -1.171, 0.524, 1.296, 0.141, 0.721], [-0.04, 4.994, 0.079, 0.373, 0.629, 0.062]] C: [[2.181, 4.661, 0.338, 1.164, 0.599, 0.637], [-0.181, 2.466, 0.019, 0.362, 0.849, 0.165], [-0.035, 1.291, 0.403, 0.392, 0.795, 0.638], [2.338, 1.45, 0.464, 0.895, 0.891, 0.816], [2.039, -1.264, 0.768, 1.237, 0.686, -0.053], [-0.249, 5.084, 0.593, 0.24, 0.421, 0.492]] D: [[1.918, 4.662, 0.478, 1.328, 0.546, 0.414], [0.093, 2.502, 0.4, 0.472, 0.776, 0.619], [0.138, 1.203, 0.414, 0.446, 0.869, 0.461], [1.918, 1.858, 0.513, 1.358, 0.507, 0.451], [2.021, -1.528, 0.41, 1.371, 0.472, 0.431], [0.209, 5.284, 0.463, 0.428, 0.778, 0.322]]
Given a RGB image and a depth image, please detect the 3D bounding box of the bench in the scene. The camera pose information includes: the rotation matrix: [[-0.482968, -0.397392, 0.78027], [-0.874514, 0.173759, -0.452807], [0.044362, -0.901048, -0.431445]]; the translation vector: [8.974016, 2.795387, 1.945192], 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: [[1.467, 4.66, 0.479, 1.188, 0.953, 0.41], [-0.153, 2.813, 0.487, 0.892, 1.061, 0.54], [0.179, 1.102, 0.898, 0.937, 1.029, 0.418], [1.771, 1.676, 0.076, 1.486, 0.58, 0.338], [1.933, -1.484, -0.005, 1.579, 0.28, 0.413], [-0.13, 5.403, 0.908, 0.195, 1.153, 0.536]] B: [[2.334, 4.242, 0.72, 1.63, 0.144, 0.491], [-0.388, 2.622, 0.373, 0.028, 1.059, 0.86], [0.405, 0.837, 0.295, 0.037, 1.048, 0.862], [2.233, 1.663, 0.713, 1.024, 0.482, 0.49], [1.733, -1.171, 0.524, 1.296, 0.141, 0.721], [-0.04, 4.994, 0.079, 0.373, 0.629, 0.062]] C: [[2.181, 4.661, 0.338, 1.164, 0.599, 0.637], [-0.181, 2.466, 0.019, 0.362, 0.849, 0.165], [-0.035, 1.291, 0.403, 0.392, 0.795, 0.638], [2.338, 1.45, 0.464, 0.895, 0.891, 0.816], [2.039, -1.264, 0.768, 1.237, 0.686, -0.053], [-0.249, 5.084, 0.593, 0.24, 0.421, 0.492]] D: [[1.918, 4.662, 0.478, 1.328, 0.546, 0.414], [0.093, 2.502, 0.4, 0.472, 0.776, 0.619], [0.138, 1.203, 0.414, 0.446, 0.869, 0.461], [1.918, 1.858, 0.513, 1.358, 0.507, 0.451], [2.021, -1.528, 0.41, 1.371, 0.472, 0.431], [0.209, 5.284, 0.463, 0.428, 0.778, 0.322]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_43_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_43_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.653, 1.297, 0.818, 0.22, 0.426, 1.095]] B: [[-1.511, 1.726, 0.43, 0.986, 0.39, 0.401]] C: [[-0.81, 1.586, -0.129, 0.278, 0.94, 0.466]] D: [[-1.238, 1.344, 0.361, 0.491, 0.703, 0.77]]
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: [[0.573165, 0.475287, -0.667521], [0.819422, -0.337921, 0.462988], [-0.005517, -0.81235, -0.583144]]; the translation vector: [4.230747, 1.597944, 1.425469], 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: [[-1.653, 1.297, 0.818, 0.22, 0.426, 1.095]] B: [[-1.511, 1.726, 0.43, 0.986, 0.39, 0.401]] C: [[-0.81, 1.586, -0.129, 0.278, 0.94, 0.466]] D: [[-1.238, 1.344, 0.361, 0.491, 0.703, 0.77]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_44_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_44_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.21, -0.485, 1.162, 0.745, 0.977, 0.286], [0.409, 1.308, 0.507, 0.07, 0.653, 0.254], [-1.112, -1.013, 0.307, 0.502, 0.872, 0.567], [-0.178, 2.738, 0.98, 0.567, 0.888, 0.53], [0.062, 1.603, 0.573, 0.692, 0.195, 0.048], [0.203, -0.892, 0.691, 0.653, 0.429, 0.535], [0.028, 1.784, 0.14, 1.147, 0.406, 0.851], [-1.458, 1.116, 0.904, -0.122, 0.156, 0.773], [-1.192, -0.149, 0.71, 0.375, 0.509, 0.581], [1.914, -2.0, 0.71, 0.384, 0.176, -0.331], [1.687, -2.156, 1.387, -0.058, 0.551, 0.368], [0.793, -1.724, 1.309, 1.148, 0.62, 0.588], [1.399, -0.955, 1.401, 0.399, 0.543, 0.388], [-0.785, -3.035, 1.174, 0.319, 0.082, 0.789], [-0.814, -2.329, 0.623, 0.245, 0.091, 0.496], [-1.62, -3.469, 0.316, 0.527, 0.537, -0.091]] B: [[-0.08, -0.154, 1.025, 0.591, 0.905, 0.775], [0.195, 0.928, 0.983, 0.833, 0.216, 0.071], [-0.777, -0.244, 0.921, 0.352, 0.434, 0.837], [-0.104, 1.99, 0.831, 0.825, 0.625, 0.159], [1.019, 2.186, 0.505, 0.763, 0.5, 0.673], [0.085, -0.695, 1.038, 0.323, 0.449, 0.684], [-0.014, 1.677, 0.448, 0.846, 0.305, -0.088], [-0.906, 1.351, 0.456, 0.541, 1.066, 0.626], [-1.282, 0.246, 0.87, 0.842, 0.096, -0.15], [1.42, -1.945, 0.918, 0.762, 0.341, 0.254], [1.009, -1.899, 1.409, -0.041, 0.531, 0.04], [0.874, -1.746, 1.047, 0.664, 0.437, 0.465], [0.723, -1.178, 0.705, 0.411, 0.715, 0.301], [-0.325, -2.808, 0.799, 0.443, 0.515, -0.023], [-1.586, -1.764, 0.236, 0.308, 0.382, 0.158], [-1.704, -3.657, 0.202, 0.579, -0.129, 0.217]] C: [[0.074, -0.449, 0.793, 0.473, 0.548, 0.492], [0.224, 1.038, 0.781, 0.486, 0.546, 0.522], [-0.941, -0.689, 0.578, 0.69, 0.615, 0.42], [-0.002, 2.387, 0.73, 0.7, 0.637, 0.471], [0.54, 1.814, 0.876, 0.434, 0.466, 0.544], [-0.295, -1.043, 0.729, 0.48, 0.533, 0.501], [-0.372, 1.676, 0.602, 0.676, 0.567, 0.405], [-1.148, 1.569, 0.485, 0.349, 0.639, 0.495], [-0.821, 0.09, 0.693, 0.409, 0.4, 0.269], [1.644, -1.897, 1.107, 0.364, 0.18, 0.12], [1.307, -2.14, 1.134, 0.414, 0.578, 0.428], [0.763, -1.797, 0.957, 0.648, 0.49, 0.409], [1.155, -1.373, 0.909, 0.317, 0.441, 0.117], [-0.563, -2.579, 0.735, 0.309, 0.521, 0.447], [-1.263, -2.059, 0.721, 0.472, 0.232, 0.232], [-1.688, -3.278, 0.604, 0.595, 0.313, 0.401]] D: [[0.369, -0.147, 1.222, 0.22, 0.106, 0.249], [0.37, 1.261, 1.11, 0.14, 1.02, 0.894], [-0.639, -0.96, 0.333, 0.677, 0.877, 0.601], [0.112, 1.921, 0.621, 0.682, 0.214, 0.04], [0.061, 1.445, 0.485, 0.375, 0.738, 0.414], [-0.478, -0.871, 0.684, 0.362, 0.566, 0.762], [-0.314, 1.927, 0.136, 0.42, 0.773, 0.685], [-1.086, 1.078, 0.616, 0.363, 0.796, 0.02], [-0.78, 0.455, 1.075, -0.039, 0.211, 0.125], [1.409, -1.503, 1.252, 0.797, 0.258, -0.146], [1.115, -1.981, 0.929, 0.053, 0.518, 0.484], [1.215, -2.2, 1.257, 0.76, 0.293, 0.427], [1.189, -1.058, 0.631, 0.369, 0.328, -0.119], [-0.365, -2.692, 1.041, -0.142, 0.542, 0.05], [-0.833, -2.437, 0.641, 0.718, 0.012, 0.121], [-2.016, -3.644, 1.062, 0.946, -0.031, -0.016]]
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: [[-0.844798, -0.442354, 0.301064], [-0.534849, 0.714819, -0.450523], [-0.015916, -0.541624, -0.84047]]; the translation vector: [3.085932, 7.995926, 1.934485], 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: [[-0.21, -0.485, 1.162, 0.745, 0.977, 0.286], [0.409, 1.308, 0.507, 0.07, 0.653, 0.254], [-1.112, -1.013, 0.307, 0.502, 0.872, 0.567], [-0.178, 2.738, 0.98, 0.567, 0.888, 0.53], [0.062, 1.603, 0.573, 0.692, 0.195, 0.048], [0.203, -0.892, 0.691, 0.653, 0.429, 0.535], [0.028, 1.784, 0.14, 1.147, 0.406, 0.851], [-1.458, 1.116, 0.904, -0.122, 0.156, 0.773], [-1.192, -0.149, 0.71, 0.375, 0.509, 0.581], [1.914, -2.0, 0.71, 0.384, 0.176, -0.331], [1.687, -2.156, 1.387, -0.058, 0.551, 0.368], [0.793, -1.724, 1.309, 1.148, 0.62, 0.588], [1.399, -0.955, 1.401, 0.399, 0.543, 0.388], [-0.785, -3.035, 1.174, 0.319, 0.082, 0.789], [-0.814, -2.329, 0.623, 0.245, 0.091, 0.496], [-1.62, -3.469, 0.316, 0.527, 0.537, -0.091]] B: [[-0.08, -0.154, 1.025, 0.591, 0.905, 0.775], [0.195, 0.928, 0.983, 0.833, 0.216, 0.071], [-0.777, -0.244, 0.921, 0.352, 0.434, 0.837], [-0.104, 1.99, 0.831, 0.825, 0.625, 0.159], [1.019, 2.186, 0.505, 0.763, 0.5, 0.673], [0.085, -0.695, 1.038, 0.323, 0.449, 0.684], [-0.014, 1.677, 0.448, 0.846, 0.305, -0.088], [-0.906, 1.351, 0.456, 0.541, 1.066, 0.626], [-1.282, 0.246, 0.87, 0.842, 0.096, -0.15], [1.42, -1.945, 0.918, 0.762, 0.341, 0.254], [1.009, -1.899, 1.409, -0.041, 0.531, 0.04], [0.874, -1.746, 1.047, 0.664, 0.437, 0.465], [0.723, -1.178, 0.705, 0.411, 0.715, 0.301], [-0.325, -2.808, 0.799, 0.443, 0.515, -0.023], [-1.586, -1.764, 0.236, 0.308, 0.382, 0.158], [-1.704, -3.657, 0.202, 0.579, -0.129, 0.217]] C: [[0.074, -0.449, 0.793, 0.473, 0.548, 0.492], [0.224, 1.038, 0.781, 0.486, 0.546, 0.522], [-0.941, -0.689, 0.578, 0.69, 0.615, 0.42], [-0.002, 2.387, 0.73, 0.7, 0.637, 0.471], [0.54, 1.814, 0.876, 0.434, 0.466, 0.544], [-0.295, -1.043, 0.729, 0.48, 0.533, 0.501], [-0.372, 1.676, 0.602, 0.676, 0.567, 0.405], [-1.148, 1.569, 0.485, 0.349, 0.639, 0.495], [-0.821, 0.09, 0.693, 0.409, 0.4, 0.269], [1.644, -1.897, 1.107, 0.364, 0.18, 0.12], [1.307, -2.14, 1.134, 0.414, 0.578, 0.428], [0.763, -1.797, 0.957, 0.648, 0.49, 0.409], [1.155, -1.373, 0.909, 0.317, 0.441, 0.117], [-0.563, -2.579, 0.735, 0.309, 0.521, 0.447], [-1.263, -2.059, 0.721, 0.472, 0.232, 0.232], [-1.688, -3.278, 0.604, 0.595, 0.313, 0.401]] D: [[0.369, -0.147, 1.222, 0.22, 0.106, 0.249], [0.37, 1.261, 1.11, 0.14, 1.02, 0.894], [-0.639, -0.96, 0.333, 0.677, 0.877, 0.601], [0.112, 1.921, 0.621, 0.682, 0.214, 0.04], [0.061, 1.445, 0.485, 0.375, 0.738, 0.414], [-0.478, -0.871, 0.684, 0.362, 0.566, 0.762], [-0.314, 1.927, 0.136, 0.42, 0.773, 0.685], [-1.086, 1.078, 0.616, 0.363, 0.796, 0.02], [-0.78, 0.455, 1.075, -0.039, 0.211, 0.125], [1.409, -1.503, 1.252, 0.797, 0.258, -0.146], [1.115, -1.981, 0.929, 0.053, 0.518, 0.484], [1.215, -2.2, 1.257, 0.76, 0.293, 0.427], [1.189, -1.058, 0.631, 0.369, 0.328, -0.119], [-0.365, -2.692, 1.041, -0.142, 0.542, 0.05], [-0.833, -2.437, 0.641, 0.718, 0.012, 0.121], [-2.016, -3.644, 1.062, 0.946, -0.031, -0.016]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_45_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_45_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.564, -1.252, 0.695, 0.857, 0.171, 1.483], [-0.805, -0.829, 1.211, 0.152, 2.16, 2.47], [-1.232, 0.204, 0.072, 0.257, 0.055, 0.162], [0.074, 0.233, 1.112, 1.831, 0.158, 2.315], [0.903, -0.43, 1.266, 0.188, 1.396, 2.012], [0.949, -1.643, 0.661, 0.101, 0.755, 1.399], [0.614, -1.995, 0.572, 0.724, 0.056, 1.162]] B: [[0.352, -1.05, 0.8, 0.589, 0.069, 1.588], [-0.381, -1.063, 0.88, -0.027, 2.004, 2.387], [-0.929, 0.409, 0.362, 0.309, 0.339, -0.301], [-0.26, 0.432, 1.078, 1.853, 0.513, 2.721], [1.171, -0.028, 1.724, -0.263, 0.948, 2.304], [1.072, -2.041, 1.024, -0.297, 0.869, 1.517], [0.352, -2.32, 0.85, 0.916, -0.424, 1.2]] C: [[0.424, -1.563, 1.009, 0.591, -0.023, 1.935], [-0.442, -0.344, 1.695, 0.23, 2.524, 2.736], [-1.205, 0.414, 0.154, -0.209, -0.177, -0.009], [-0.098, 0.328, 1.36, 1.735, 0.101, 1.922], [0.835, -0.195, 1.265, 0.532, 0.907, 2.267], [1.354, -1.455, 1.149, 0.399, 0.893, 1.521], [0.733, -1.909, 0.585, 1.055, -0.351, 1.621]] D: [[0.598, -1.618, 0.741, 0.612, 0.383, 1.422], [-0.532, -0.954, 1.597, 0.537, 2.362, 2.085], [-0.843, 0.31, -0.092, 0.065, -0.048, 0.556], [0.212, 0.31, 0.904, 1.605, 0.458, 1.973], [0.493, -0.221, 1.142, 0.015, 1.45, 2.441], [1.383, -2.104, 0.997, -0.035, 0.835, 1.803], [0.664, -2.077, 1.046, 1.1, 0.235, 1.396]]
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: [[0.982764, 0.054289, -0.17671], [0.184841, -0.27426, 0.943724], [0.002769, -0.960122, -0.279568]]; the translation vector: [4.072058, 1.220293, 1.47625], 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: [[0.564, -1.252, 0.695, 0.857, 0.171, 1.483], [-0.805, -0.829, 1.211, 0.152, 2.16, 2.47], [-1.232, 0.204, 0.072, 0.257, 0.055, 0.162], [0.074, 0.233, 1.112, 1.831, 0.158, 2.315], [0.903, -0.43, 1.266, 0.188, 1.396, 2.012], [0.949, -1.643, 0.661, 0.101, 0.755, 1.399], [0.614, -1.995, 0.572, 0.724, 0.056, 1.162]] B: [[0.352, -1.05, 0.8, 0.589, 0.069, 1.588], [-0.381, -1.063, 0.88, -0.027, 2.004, 2.387], [-0.929, 0.409, 0.362, 0.309, 0.339, -0.301], [-0.26, 0.432, 1.078, 1.853, 0.513, 2.721], [1.171, -0.028, 1.724, -0.263, 0.948, 2.304], [1.072, -2.041, 1.024, -0.297, 0.869, 1.517], [0.352, -2.32, 0.85, 0.916, -0.424, 1.2]] C: [[0.424, -1.563, 1.009, 0.591, -0.023, 1.935], [-0.442, -0.344, 1.695, 0.23, 2.524, 2.736], [-1.205, 0.414, 0.154, -0.209, -0.177, -0.009], [-0.098, 0.328, 1.36, 1.735, 0.101, 1.922], [0.835, -0.195, 1.265, 0.532, 0.907, 2.267], [1.354, -1.455, 1.149, 0.399, 0.893, 1.521], [0.733, -1.909, 0.585, 1.055, -0.351, 1.621]] D: [[0.598, -1.618, 0.741, 0.612, 0.383, 1.422], [-0.532, -0.954, 1.597, 0.537, 2.362, 2.085], [-0.843, 0.31, -0.092, 0.065, -0.048, 0.556], [0.212, 0.31, 0.904, 1.605, 0.458, 1.973], [0.493, -0.221, 1.142, 0.015, 1.45, 2.441], [1.383, -2.104, 0.997, -0.035, 0.835, 1.803], [0.664, -2.077, 1.046, 1.1, 0.235, 1.396]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_46_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_46_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.784, -1.767, 0.476, 0.231, 0.24, 0.946], [-0.366, -0.774, 1.245, 0.024, 1.212, 0.879], [0.003, -1.957, 1.089, 0.298, 0.345, 0.685], [0.22, -0.648, 1.189, -0.053, 1.037, 0.737]] B: [[0.318, -1.739, 0.9, 0.365, 0.659, 0.502], [-0.143, -0.934, 0.904, 0.311, 0.754, 0.487], [-0.263, -1.46, 0.926, 0.248, 0.697, 0.452], [0.319, -1.069, 0.941, 0.277, 0.615, 0.5]] C: [[0.289, -1.409, 1.144, 0.67, 0.233, 0.02], [0.068, -0.634, 0.752, -0.119, 1.056, 0.899], [0.211, -1.754, 1.05, -0.206, 0.931, 0.732], [-0.148, -1.524, 1.046, -0.083, 1.07, 0.467]] D: [[0.118, -1.502, 0.988, 0.826, 0.676, 0.125], [-0.431, -1.392, 0.927, 0.243, 0.317, 0.128], [-0.041, -1.634, 0.476, -0.222, 0.764, 0.802], [0.199, -1.056, 1.182, 0.1, 0.287, 0.626]]
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: [[-0.481759, -0.460793, 0.745371], [-0.875469, 0.290199, -0.386444], [-0.038235, -0.838722, -0.543216]]; the translation vector: [3.08436, 2.075189, 1.468295], 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: [[0.784, -1.767, 0.476, 0.231, 0.24, 0.946], [-0.366, -0.774, 1.245, 0.024, 1.212, 0.879], [0.003, -1.957, 1.089, 0.298, 0.345, 0.685], [0.22, -0.648, 1.189, -0.053, 1.037, 0.737]] B: [[0.318, -1.739, 0.9, 0.365, 0.659, 0.502], [-0.143, -0.934, 0.904, 0.311, 0.754, 0.487], [-0.263, -1.46, 0.926, 0.248, 0.697, 0.452], [0.319, -1.069, 0.941, 0.277, 0.615, 0.5]] C: [[0.289, -1.409, 1.144, 0.67, 0.233, 0.02], [0.068, -0.634, 0.752, -0.119, 1.056, 0.899], [0.211, -1.754, 1.05, -0.206, 0.931, 0.732], [-0.148, -1.524, 1.046, -0.083, 1.07, 0.467]] D: [[0.118, -1.502, 0.988, 0.826, 0.676, 0.125], [-0.431, -1.392, 0.927, 0.243, 0.317, 0.128], [-0.041, -1.634, 0.476, -0.222, 0.764, 0.802], [0.199, -1.056, 1.182, 0.1, 0.287, 0.626]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_47_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_47_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.668, 1.082, 1.323, 0.017, 1.605, 2.936], [2.048, 0.314, 0.42, 0.03, 0.539, 1.761], [1.696, -0.749, 1.568, 0.626, 3.055, 2.333], [0.245, -2.087, 0.863, 3.306, 0.237, 1.624], [-1.623, -0.389, 0.569, -0.197, 4.462, 2.242], [-0.209, 2.531, 1.246, 3.173, 0.694, 2.668]] B: [[2.245, 1.07, 1.564, -0.254, 1.675, 2.343], [1.954, 0.142, 1.271, 0.081, 0.135, 1.547], [1.76, -0.992, 1.136, -0.068, 2.332, 2.454], [-0.223, -2.118, 0.902, 3.53, 0.211, 2.156], [-1.973, 0.007, 0.511, -0.091, 4.007, 2.11], [0.095, 1.842, 1.661, 2.856, 0.289, 2.599]] C: [[1.954, 0.955, 1.134, 0.469, 1.906, 3.136], [2.108, 0.777, 1.024, 0.49, 0.432, 1.736], [1.804, -1.161, 1.159, 0.579, 2.431, 2.741], [-0.075, -2.215, 1.141, 4.022, 0.647, 1.726], [-1.259, -0.097, 0.765, 0.259, 4.315, 1.492], [0.085, 2.397, 1.377, 2.831, 0.531, 2.459]] D: [[1.757, 1.207, 1.277, 0.171, 1.443, 2.662], [1.938, 0.553, 0.792, 0.372, 0.083, 1.699], [2.057, -0.732, 1.221, 0.308, 2.678, 2.532], [0.254, -2.161, 1.253, 3.68, 0.191, 2.014], [-1.595, -0.042, 0.831, 0.273, 4.363, 1.747], [0.19, 2.052, 1.297, 3.302, 0.408, 2.639]]
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: [[-0.935878, -0.161972, 0.312885], [-0.352322, 0.433116, -0.829627], [-0.001139, -0.886666, -0.46241]]; the translation vector: [1.123681, 2.231354, 1.408983], 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: [[1.668, 1.082, 1.323, 0.017, 1.605, 2.936], [2.048, 0.314, 0.42, 0.03, 0.539, 1.761], [1.696, -0.749, 1.568, 0.626, 3.055, 2.333], [0.245, -2.087, 0.863, 3.306, 0.237, 1.624], [-1.623, -0.389, 0.569, -0.197, 4.462, 2.242], [-0.209, 2.531, 1.246, 3.173, 0.694, 2.668]] B: [[2.245, 1.07, 1.564, -0.254, 1.675, 2.343], [1.954, 0.142, 1.271, 0.081, 0.135, 1.547], [1.76, -0.992, 1.136, -0.068, 2.332, 2.454], [-0.223, -2.118, 0.902, 3.53, 0.211, 2.156], [-1.973, 0.007, 0.511, -0.091, 4.007, 2.11], [0.095, 1.842, 1.661, 2.856, 0.289, 2.599]] C: [[1.954, 0.955, 1.134, 0.469, 1.906, 3.136], [2.108, 0.777, 1.024, 0.49, 0.432, 1.736], [1.804, -1.161, 1.159, 0.579, 2.431, 2.741], [-0.075, -2.215, 1.141, 4.022, 0.647, 1.726], [-1.259, -0.097, 0.765, 0.259, 4.315, 1.492], [0.085, 2.397, 1.377, 2.831, 0.531, 2.459]] D: [[1.757, 1.207, 1.277, 0.171, 1.443, 2.662], [1.938, 0.553, 0.792, 0.372, 0.083, 1.699], [2.057, -0.732, 1.221, 0.308, 2.678, 2.532], [0.254, -2.161, 1.253, 3.68, 0.191, 2.014], [-1.595, -0.042, 0.831, 0.273, 4.363, 1.747], [0.19, 2.052, 1.297, 3.302, 0.408, 2.639]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_48_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_48_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.874, 0.432, 0.675, 0.547, 4.466, 2.765], [2.077, 1.025, 0.96, 0.435, 5.53, 2.428], [-0.302, -2.355, 0.907, 2.255, -0.132, 2.065], [1.309, 2.97, 0.649, 2.105, 0.601, 1.706], [1.394, -2.794, 0.572, 0.929, 0.444, 0.269]] B: [[-1.774, -0.336, 1.363, 0.137, 4.327, 2.118], [2.024, 0.331, 0.678, 0.299, 6.038, 2.411], [-0.973, -2.453, 1.173, 2.209, -0.12, 1.889], [0.907, 3.079, 0.375, 1.445, 0.297, 1.527], [1.457, -2.684, 0.632, 0.896, -0.39, 0.289]] C: [[-2.285, -0.2, 1.099, -0.248, 4.908, 2.313], [2.096, 0.355, 1.235, 0.363, 5.974, 2.044], [-1.085, -2.082, 0.91, 2.454, 0.239, 1.438], [0.732, 3.157, 0.493, 1.665, 0.182, 1.592], [1.088, -2.467, -0.003, 0.673, 0.233, 0.167]] D: [[-1.815, -0.066, 1.137, 0.19, 4.502, 2.283], [1.738, 0.547, 0.94, 0.42, 5.701, 2.065], [-0.777, -2.286, 1.047, 2.091, 0.123, 1.885], [1.023, 3.389, 0.735, 1.699, 0.123, 1.528], [1.495, -2.301, 0.226, 0.722, 0.028, 0.613]]
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: [[0.934222, -0.219071, 0.281493], [-0.356558, -0.595286, 0.72007], [0.009823, -0.773073, -0.634241]]; the translation vector: [0.331108, 1.989283, 1.551545], 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: [[-1.874, 0.432, 0.675, 0.547, 4.466, 2.765], [2.077, 1.025, 0.96, 0.435, 5.53, 2.428], [-0.302, -2.355, 0.907, 2.255, -0.132, 2.065], [1.309, 2.97, 0.649, 2.105, 0.601, 1.706], [1.394, -2.794, 0.572, 0.929, 0.444, 0.269]] B: [[-1.774, -0.336, 1.363, 0.137, 4.327, 2.118], [2.024, 0.331, 0.678, 0.299, 6.038, 2.411], [-0.973, -2.453, 1.173, 2.209, -0.12, 1.889], [0.907, 3.079, 0.375, 1.445, 0.297, 1.527], [1.457, -2.684, 0.632, 0.896, -0.39, 0.289]] C: [[-2.285, -0.2, 1.099, -0.248, 4.908, 2.313], [2.096, 0.355, 1.235, 0.363, 5.974, 2.044], [-1.085, -2.082, 0.91, 2.454, 0.239, 1.438], [0.732, 3.157, 0.493, 1.665, 0.182, 1.592], [1.088, -2.467, -0.003, 0.673, 0.233, 0.167]] D: [[-1.815, -0.066, 1.137, 0.19, 4.502, 2.283], [1.738, 0.547, 0.94, 0.42, 5.701, 2.065], [-0.777, -2.286, 1.047, 2.091, 0.123, 1.885], [1.023, 3.389, 0.735, 1.699, 0.123, 1.528], [1.495, -2.301, 0.226, 0.722, 0.028, 0.613]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_49_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_49_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.355, 0.849, 0.484, 0.583, 0.026, -0.166]] B: [[-0.954, 0.48, 0.115, 0.22, 0.221, 0.246]] C: [[-0.886, 0.23, -0.323, 0.388, 0.524, 0.544]] D: [[-0.877, -0.009, -0.082, -0.196, 0.347, 0.57]]
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: [[-0.986418, -0.051155, 0.156087], [-0.152905, 0.633099, -0.758819], [-0.060001, -0.772379, -0.632322]]; the translation vector: [2.055195, 1.600374, 1.268236], 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: [[-1.355, 0.849, 0.484, 0.583, 0.026, -0.166]] B: [[-0.954, 0.48, 0.115, 0.22, 0.221, 0.246]] C: [[-0.886, 0.23, -0.323, 0.388, 0.524, 0.544]] D: [[-0.877, -0.009, -0.082, -0.196, 0.347, 0.57]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_50_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_50_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.231, -1.891, 1.007, 2.627, 2.266, 2.036], [-0.307, -0.367, 0.926, 1.513, 1.063, 1.867]] B: [[0.718, -2.089, 0.687, 2.342, 2.265, 1.579], [-0.634, -0.345, 1.176, 1.11, 1.202, 2.075]] C: [[0.464, -1.663, 1.056, 2.135, 2.464, 2.098], [-0.781, -0.219, 1.071, 1.18, 1.361, 1.522]] D: [[-0.112, -2.192, 0.852, 2.525, 1.965, 2.377], [0.128, -0.805, 0.888, 1.396, 1.418, 2.338]]
Given a RGB image and a depth image, please detect the 3D bounding box of the bathroom stall in the scene. The camera pose information includes: the rotation matrix: [[-0.255252, -0.433184, 0.864406], [-0.966562, 0.137073, -0.216725], [-0.024605, -0.890821, -0.453687]]; the translation vector: [1.468232, 3.881342, 1.432686], 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: [[0.231, -1.891, 1.007, 2.627, 2.266, 2.036], [-0.307, -0.367, 0.926, 1.513, 1.063, 1.867]] B: [[0.718, -2.089, 0.687, 2.342, 2.265, 1.579], [-0.634, -0.345, 1.176, 1.11, 1.202, 2.075]] C: [[0.464, -1.663, 1.056, 2.135, 2.464, 2.098], [-0.781, -0.219, 1.071, 1.18, 1.361, 1.522]] D: [[-0.112, -2.192, 0.852, 2.525, 1.965, 2.377], [0.128, -0.805, 0.888, 1.396, 1.418, 2.338]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_51_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_51_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.293, -1.301, 1.261, 0.557, 0.076, 0.181]] B: [[-2.3, -0.603, 0.539, 0.144, 0.291, 0.744]] C: [[-2.289, -1.004, 0.913, 0.094, 0.463, 0.318]] D: [[-2.447, -0.778, 0.56, -0.086, 0.586, 0.687]]
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: [[0.140295, 0.625342, -0.767636], [0.990108, -0.090149, 0.107516], [-0.001967, -0.775126, -0.631804]]; the translation vector: [3.410891, 3.073526, 1.198756], 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: [[-2.293, -1.301, 1.261, 0.557, 0.076, 0.181]] B: [[-2.3, -0.603, 0.539, 0.144, 0.291, 0.744]] C: [[-2.289, -1.004, 0.913, 0.094, 0.463, 0.318]] D: [[-2.447, -0.778, 0.56, -0.086, 0.586, 0.687]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_52_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_52_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.354, 0.454, 0.921, -0.335, 0.498, 0.874], [0.185, -0.574, 0.751, 0.09, -0.38, 0.911], [0.667, 0.586, 2.143, 0.441, 0.23, 0.505]] B: [[-1.09, 0.059, 1.019, 0.117, 0.263, 0.377], [0.279, -1.061, 0.877, 0.477, 0.116, 0.622], [0.666, 0.093, 1.789, 0.132, 0.373, 0.347]] C: [[-1.434, -0.263, 0.532, 0.445, 0.024, 0.383], [-0.034, -1.535, 0.533, 0.655, 0.426, 0.876], [0.704, 0.231, 1.687, 0.279, -0.11, 0.575]] D: [[-0.897, -0.345, 1.454, 0.607, 0.705, 0.804], [0.146, -1.337, 0.587, 0.096, 0.382, 0.839], [0.567, -0.339, 1.673, 0.166, 0.534, 0.522]]
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: [[-0.221984, 0.421429, -0.879273], [0.97466, 0.121427, -0.187867], [0.027595, -0.898695, -0.437705]]; the translation vector: [3.155292, 0.483793, 1.35371], 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: [[-1.354, 0.454, 0.921, -0.335, 0.498, 0.874], [0.185, -0.574, 0.751, 0.09, -0.38, 0.911], [0.667, 0.586, 2.143, 0.441, 0.23, 0.505]] B: [[-1.09, 0.059, 1.019, 0.117, 0.263, 0.377], [0.279, -1.061, 0.877, 0.477, 0.116, 0.622], [0.666, 0.093, 1.789, 0.132, 0.373, 0.347]] C: [[-1.434, -0.263, 0.532, 0.445, 0.024, 0.383], [-0.034, -1.535, 0.533, 0.655, 0.426, 0.876], [0.704, 0.231, 1.687, 0.279, -0.11, 0.575]] D: [[-0.897, -0.345, 1.454, 0.607, 0.705, 0.804], [0.146, -1.337, 0.587, 0.096, 0.382, 0.839], [0.567, -0.339, 1.673, 0.166, 0.534, 0.522]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_53_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_53_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.872, -1.053, 1.714, -0.4, 0.547, -0.388]] B: [[-0.641, -0.865, 2.002, 0.06, 0.688, 0.05]] C: [[-0.24, -0.538, 2.349, -0.015, 0.604, 0.452]] D: [[-0.437, -0.89, 1.743, -0.382, 0.608, -0.394]]
Given a RGB image and a depth image, please detect the 3D bounding box of the shower curtain rod in the scene. The camera pose information includes: the rotation matrix: [[0.173351, 0.592298, -0.78685], [0.984858, -0.105806, 0.137329], [-0.001913, -0.798742, -0.601671]]; the translation vector: [3.264189, 1.940071, 1.28435], 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: [[-0.872, -1.053, 1.714, -0.4, 0.547, -0.388]] B: [[-0.641, -0.865, 2.002, 0.06, 0.688, 0.05]] C: [[-0.24, -0.538, 2.349, -0.015, 0.604, 0.452]] D: [[-0.437, -0.89, 1.743, -0.382, 0.608, -0.394]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_54_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_54_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.74, 0.949, 0.805, 2.053, 0.051, 1.667], [-1.281, -0.065, 0.899, 0.112, 2.004, 1.85], [0.446, -1.039, 0.627, 1.399, 0.094, 1.27], [1.134, -0.792, 0.678, 0.041, 0.539, 1.365], [-1.434, 2.505, 0.652, 0.518, 0.203, 1.213]] B: [[1.029, 0.71, 0.916, 2.029, -0.176, 1.869], [-1.683, -0.445, 1.099, -0.259, 2.235, 1.713], [0.848, -1.08, 0.506, 1.798, 0.259, 1.153], [1.268, -0.42, 0.271, 0.287, 0.751, 1.048], [-1.043, 2.825, 0.333, 0.321, -0.246, 1.582]] C: [[0.966, 1.169, 0.637, 2.193, -0.193, 1.801], [-0.869, -0.535, 1.386, 0.092, 1.727, 2.164], [0.169, -1.108, 0.224, 1.056, -0.222, 1.304], [0.91, -1.037, 1.17, -0.025, 0.5, 1.639], [-0.958, 2.714, 0.971, 0.285, -0.285, 1.316]] D: [[0.741, 1.382, 0.663, 1.864, -0.249, 2.055], [-1.139, 0.311, 1.207, -0.23, 2.288, 2.067], [0.431, -1.158, 0.998, 1.247, 0.194, 1.309], [0.658, -1.111, 1.067, 0.365, 0.642, 0.899], [-1.437, 2.999, 0.509, 0.702, 0.182, 1.021]]
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: [[0.660671, 0.426343, -0.617856], [0.749322, -0.423957, 0.508701], [-0.045063, -0.799057, -0.599565]]; the translation vector: [1.739014, 2.260029, 1.323145], 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: [[0.74, 0.949, 0.805, 2.053, 0.051, 1.667], [-1.281, -0.065, 0.899, 0.112, 2.004, 1.85], [0.446, -1.039, 0.627, 1.399, 0.094, 1.27], [1.134, -0.792, 0.678, 0.041, 0.539, 1.365], [-1.434, 2.505, 0.652, 0.518, 0.203, 1.213]] B: [[1.029, 0.71, 0.916, 2.029, -0.176, 1.869], [-1.683, -0.445, 1.099, -0.259, 2.235, 1.713], [0.848, -1.08, 0.506, 1.798, 0.259, 1.153], [1.268, -0.42, 0.271, 0.287, 0.751, 1.048], [-1.043, 2.825, 0.333, 0.321, -0.246, 1.582]] C: [[0.966, 1.169, 0.637, 2.193, -0.193, 1.801], [-0.869, -0.535, 1.386, 0.092, 1.727, 2.164], [0.169, -1.108, 0.224, 1.056, -0.222, 1.304], [0.91, -1.037, 1.17, -0.025, 0.5, 1.639], [-0.958, 2.714, 0.971, 0.285, -0.285, 1.316]] D: [[0.741, 1.382, 0.663, 1.864, -0.249, 2.055], [-1.139, 0.311, 1.207, -0.23, 2.288, 2.067], [0.431, -1.158, 0.998, 1.247, 0.194, 1.309], [0.658, -1.111, 1.067, 0.365, 0.642, 0.899], [-1.437, 2.999, 0.509, 0.702, 0.182, 1.021]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_55_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_55_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[2.289, 1.091, 1.235, 0.312, 0.445, 0.181], [2.614, -0.282, 1.115, 0.396, 0.952, 0.37], [2.915, -1.131, 1.323, 0.416, 1.127, 0.582]] B: [[2.865, 1.27, 1.277, 0.662, 1.126, 0.413], [2.634, -0.253, 1.185, 0.725, 0.57, 0.723], [2.702, -0.759, 1.232, 0.075, 0.776, 0.187]] C: [[2.596, 1.198, 1.179, 0.402, 0.868, 0.166], [2.565, 0.04, 1.202, 0.364, 0.895, 0.33], [2.601, -1.116, 1.104, 0.457, 0.792, 0.155]] D: [[2.413, 1.176, 1.278, 0.589, 0.574, -0.073], [2.181, 0.298, 1.094, 0.783, 1.368, 0.634], [2.395, -1.077, 1.082, 0.598, 1.002, 0.39]]
Given a RGB image and a depth image, please detect the 3D bounding box of the windowsill in the scene. The camera pose information includes: the rotation matrix: [[0.606468, -0.360414, 0.70873], [-0.789578, -0.16805, 0.590192], [-0.093612, -0.91753, -0.386492]]; the translation vector: [2.373669, 6.226582, 1.48631], 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: [[2.289, 1.091, 1.235, 0.312, 0.445, 0.181], [2.614, -0.282, 1.115, 0.396, 0.952, 0.37], [2.915, -1.131, 1.323, 0.416, 1.127, 0.582]] B: [[2.865, 1.27, 1.277, 0.662, 1.126, 0.413], [2.634, -0.253, 1.185, 0.725, 0.57, 0.723], [2.702, -0.759, 1.232, 0.075, 0.776, 0.187]] C: [[2.596, 1.198, 1.179, 0.402, 0.868, 0.166], [2.565, 0.04, 1.202, 0.364, 0.895, 0.33], [2.601, -1.116, 1.104, 0.457, 0.792, 0.155]] D: [[2.413, 1.176, 1.278, 0.589, 0.574, -0.073], [2.181, 0.298, 1.094, 0.783, 1.368, 0.634], [2.395, -1.077, 1.082, 0.598, 1.002, 0.39]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_56_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_56_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.001, 2.948, 0.696, 1.051, 0.653, 1.017], [-1.218, 2.566, 0.334, 0.65, 1.143, 0.576], [-1.049, 4.68, 0.409, 0.92, 0.545, 1.203], [-0.848, -3.875, 0.54, 0.615, 0.936, 1.037], [1.041, 2.41, 0.443, 0.89, 0.787, 0.94], [1.624, -1.213, 0.004, 1.481, 1.102, 0.478], [1.287, 1.232, 0.545, 1.204, 1.228, 0.841], [1.818, -0.113, 0.532, 0.874, 0.706, 1.086], [0.092, -5.089, 0.693, 0.961, 0.819, 0.322], [-0.468, -1.491, 0.774, 0.97, 1.2, 1.024]] B: [[-0.126, 2.459, 0.086, 0.932, 1.114, 1.123], [-0.966, 2.226, 0.359, 1.537, 0.757, 0.462], [-1.21, 4.954, 0.104, 1.239, 0.624, 0.543], [-0.516, -4.249, 0.544, 1.157, 1.197, 1.269], [1.294, 2.428, 0.861, 1.276, 0.579, 0.451], [1.569, -1.608, 0.36, 0.726, 1.508, 0.636], [0.656, 1.11, -0.004, 0.679, 1.224, 0.752], [0.999, -0.375, 0.707, 0.664, 1.131, 0.788], [0.529, -5.125, 0.2, 0.899, 0.951, 0.927], [-1.058, -1.898, 0.447, 0.976, 1.149, 0.369]] C: [[0.237, 2.908, 0.463, 0.898, 0.83, 0.718], [-0.876, 2.53, 0.52, 1.072, 0.924, 0.781], [-1.088, 4.721, 0.492, 0.991, 0.901, 0.767], [-0.583, -3.833, 0.327, 0.92, 0.918, 0.773], [1.47, 1.953, 0.456, 0.894, 0.96, 0.795], [1.829, -1.442, 0.405, 1.045, 1.024, 0.748], [1.035, 0.766, 0.48, 0.857, 0.923, 0.799], [1.416, -0.318, 0.434, 1.021, 0.961, 0.774], [0.375, -5.051, 0.244, 0.861, 0.856, 0.761], [-0.588, -1.854, 0.411, 0.932, 0.952, 0.73]] D: [[0.31, 2.967, 0.642, 1.326, 0.654, 0.284], [-1.165, 2.181, 0.237, 1.304, 0.639, 0.395], [-0.721, 4.769, 0.925, 1.219, 0.928, 0.661], [-1.026, -3.416, 0.149, 0.806, 0.901, 0.778], [1.652, 1.761, 0.169, 1.115, 0.472, 1.022], [2.158, -1.036, 0.663, 0.749, 0.724, 1.014], [0.591, 0.853, 0.97, 1.294, 0.724, 0.816], [1.34, 0.03, 0.19, 1.304, 0.703, 0.552], [0.387, -4.975, 0.689, 0.413, 1.29, 0.685], [-0.424, -1.902, 0.121, 1.041, 0.562, 0.86]]
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: [[0.974605, -0.106498, 0.196986], [-0.223762, -0.428932, 0.875185], [-0.008712, -0.897037, -0.44187]]; the translation vector: [2.006689, 0.552817, 1.711334], 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: [[-0.001, 2.948, 0.696, 1.051, 0.653, 1.017], [-1.218, 2.566, 0.334, 0.65, 1.143, 0.576], [-1.049, 4.68, 0.409, 0.92, 0.545, 1.203], [-0.848, -3.875, 0.54, 0.615, 0.936, 1.037], [1.041, 2.41, 0.443, 0.89, 0.787, 0.94], [1.624, -1.213, 0.004, 1.481, 1.102, 0.478], [1.287, 1.232, 0.545, 1.204, 1.228, 0.841], [1.818, -0.113, 0.532, 0.874, 0.706, 1.086], [0.092, -5.089, 0.693, 0.961, 0.819, 0.322], [-0.468, -1.491, 0.774, 0.97, 1.2, 1.024]] B: [[-0.126, 2.459, 0.086, 0.932, 1.114, 1.123], [-0.966, 2.226, 0.359, 1.537, 0.757, 0.462], [-1.21, 4.954, 0.104, 1.239, 0.624, 0.543], [-0.516, -4.249, 0.544, 1.157, 1.197, 1.269], [1.294, 2.428, 0.861, 1.276, 0.579, 0.451], [1.569, -1.608, 0.36, 0.726, 1.508, 0.636], [0.656, 1.11, -0.004, 0.679, 1.224, 0.752], [0.999, -0.375, 0.707, 0.664, 1.131, 0.788], [0.529, -5.125, 0.2, 0.899, 0.951, 0.927], [-1.058, -1.898, 0.447, 0.976, 1.149, 0.369]] C: [[0.237, 2.908, 0.463, 0.898, 0.83, 0.718], [-0.876, 2.53, 0.52, 1.072, 0.924, 0.781], [-1.088, 4.721, 0.492, 0.991, 0.901, 0.767], [-0.583, -3.833, 0.327, 0.92, 0.918, 0.773], [1.47, 1.953, 0.456, 0.894, 0.96, 0.795], [1.829, -1.442, 0.405, 1.045, 1.024, 0.748], [1.035, 0.766, 0.48, 0.857, 0.923, 0.799], [1.416, -0.318, 0.434, 1.021, 0.961, 0.774], [0.375, -5.051, 0.244, 0.861, 0.856, 0.761], [-0.588, -1.854, 0.411, 0.932, 0.952, 0.73]] D: [[0.31, 2.967, 0.642, 1.326, 0.654, 0.284], [-1.165, 2.181, 0.237, 1.304, 0.639, 0.395], [-0.721, 4.769, 0.925, 1.219, 0.928, 0.661], [-1.026, -3.416, 0.149, 0.806, 0.901, 0.778], [1.652, 1.761, 0.169, 1.115, 0.472, 1.022], [2.158, -1.036, 0.663, 0.749, 0.724, 1.014], [0.591, 0.853, 0.97, 1.294, 0.724, 0.816], [1.34, 0.03, 0.19, 1.304, 0.703, 0.552], [0.387, -4.975, 0.689, 0.413, 1.29, 0.685], [-0.424, -1.902, 0.121, 1.041, 0.562, 0.86]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_57_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_57_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.945, -0.877, -0.123, 1.546, 1.347, 0.112]] B: [[0.857, -1.188, 0.118, 1.684, 1.025, 0.263]] C: [[0.995, -0.398, -0.499, 1.213, 1.119, -0.036]] D: [[0.539, -0.587, -0.275, 1.351, 1.1, -0.319]]
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: [[-0.693623, 0.392298, -0.604144], [0.720137, 0.397492, -0.568686], [0.017048, -0.82952, -0.558217]]; the translation vector: [2.706242, 2.586761, 1.453005], 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: [[0.945, -0.877, -0.123, 1.546, 1.347, 0.112]] B: [[0.857, -1.188, 0.118, 1.684, 1.025, 0.263]] C: [[0.995, -0.398, -0.499, 1.213, 1.119, -0.036]] D: [[0.539, -0.587, -0.275, 1.351, 1.1, -0.319]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_58_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_58_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.143, 1.575, 0.04, 0.27, 0.312, 0.15], [-0.377, 3.615, 0.346, 0.295, 0.569, 0.473], [-1.45, 0.655, 0.569, 0.701, 0.954, 0.318], [2.369, -0.854, 0.716, 0.861, 0.372, 0.384], [3.488, -0.639, 0.515, 0.374, 0.717, 0.642], [3.31, -2.144, 0.849, 0.423, 1.039, 0.351], [3.753, -1.021, 0.778, 0.709, 0.641, 0.792], [-1.949, 2.854, 0.124, 0.704, 0.146, 0.084]] B: [[-1.76, 1.841, 0.53, 0.73, 0.674, 0.544], [-0.679, 3.307, 0.476, 0.669, 0.734, 0.506], [-1.7, 0.568, 0.465, 0.694, 0.62, 0.52], [2.474, -1.195, 0.409, 0.606, 0.509, 0.689], [3.174, -0.614, 0.339, 0.542, 0.599, 0.782], [3.186, -2.158, 0.546, 0.503, 0.633, 0.516], [3.901, -1.236, 0.485, 0.592, 0.545, 0.635], [-1.787, 2.437, 0.508, 0.713, 0.589, 0.468]] C: [[-2.143, 1.685, 0.995, 0.615, 0.904, 0.263], [-1.005, 3.628, 0.394, 0.466, 0.405, 0.998], [-2.179, 0.615, 0.333, 0.233, 0.298, 0.889], [2.014, -1.057, 0.599, 0.68, 0.338, 0.974], [2.918, -0.471, 0.1, 0.575, 0.71, 0.376], [3.127, -2.436, 0.498, 0.497, 0.327, 0.902], [3.486, -1.558, 0.63, 0.593, 0.23, 0.81], [-1.407, 2.857, 0.881, 0.499, 1.07, 0.68]] D: [[-1.261, 2.229, 0.998, 1.215, 1.048, 0.703], [-1.092, 3.457, -0.005, 0.668, 1.114, 0.663], [-1.477, 0.865, 0.817, 0.301, 0.363, 0.292], [2.93, -1.308, 0.561, 1.073, 0.232, 1.069], [3.634, -0.503, -0.085, 0.796, 0.476, 0.342], [3.396, -2.322, 0.932, 0.945, 0.812, 0.616], [4.075, -1.495, 0.312, 0.703, 0.562, 0.973], [-2.275, 2.728, 0.786, 0.449, 0.77, 0.134]]
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: [[-0.891251, 0.378307, -0.25011], [0.443048, 0.608538, -0.658323], [-0.096846, -0.697542, -0.709969]]; the translation vector: [4.935522, 3.588868, 1.45033], 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: [[-2.143, 1.575, 0.04, 0.27, 0.312, 0.15], [-0.377, 3.615, 0.346, 0.295, 0.569, 0.473], [-1.45, 0.655, 0.569, 0.701, 0.954, 0.318], [2.369, -0.854, 0.716, 0.861, 0.372, 0.384], [3.488, -0.639, 0.515, 0.374, 0.717, 0.642], [3.31, -2.144, 0.849, 0.423, 1.039, 0.351], [3.753, -1.021, 0.778, 0.709, 0.641, 0.792], [-1.949, 2.854, 0.124, 0.704, 0.146, 0.084]] B: [[-1.76, 1.841, 0.53, 0.73, 0.674, 0.544], [-0.679, 3.307, 0.476, 0.669, 0.734, 0.506], [-1.7, 0.568, 0.465, 0.694, 0.62, 0.52], [2.474, -1.195, 0.409, 0.606, 0.509, 0.689], [3.174, -0.614, 0.339, 0.542, 0.599, 0.782], [3.186, -2.158, 0.546, 0.503, 0.633, 0.516], [3.901, -1.236, 0.485, 0.592, 0.545, 0.635], [-1.787, 2.437, 0.508, 0.713, 0.589, 0.468]] C: [[-2.143, 1.685, 0.995, 0.615, 0.904, 0.263], [-1.005, 3.628, 0.394, 0.466, 0.405, 0.998], [-2.179, 0.615, 0.333, 0.233, 0.298, 0.889], [2.014, -1.057, 0.599, 0.68, 0.338, 0.974], [2.918, -0.471, 0.1, 0.575, 0.71, 0.376], [3.127, -2.436, 0.498, 0.497, 0.327, 0.902], [3.486, -1.558, 0.63, 0.593, 0.23, 0.81], [-1.407, 2.857, 0.881, 0.499, 1.07, 0.68]] D: [[-1.261, 2.229, 0.998, 1.215, 1.048, 0.703], [-1.092, 3.457, -0.005, 0.668, 1.114, 0.663], [-1.477, 0.865, 0.817, 0.301, 0.363, 0.292], [2.93, -1.308, 0.561, 1.073, 0.232, 1.069], [3.634, -0.503, -0.085, 0.796, 0.476, 0.342], [3.396, -2.322, 0.932, 0.945, 0.812, 0.616], [4.075, -1.495, 0.312, 0.703, 0.562, 0.973], [-2.275, 2.728, 0.786, 0.449, 0.77, 0.134]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_59_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_59_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.205, 1.797, 1.094, 1.154, 0.654, 1.112], [0.658, 1.295, 1.132, 1.277, 0.037, 0.601]] B: [[-0.63, 1.531, 1.06, 1.175, 0.329, 0.727], [0.734, 1.578, 0.984, 1.15, 0.266, 0.361]] C: [[-0.726, 1.106, 1.434, 1.522, 0.658, 0.308], [1.201, 1.481, 1.246, 0.828, 0.067, 0.371]] D: [[-0.719, 1.086, 1.264, 0.78, 0.793, 0.35], [0.868, 1.98, 0.75, 1.049, 0.201, 0.363]]
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: [[0.081815, 0.638296, -0.765431], [0.996577, -0.061545, 0.055199], [-0.011875, -0.767327, -0.641146]]; the translation vector: [3.004073, 1.570726, 1.431248], 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: [[-0.205, 1.797, 1.094, 1.154, 0.654, 1.112], [0.658, 1.295, 1.132, 1.277, 0.037, 0.601]] B: [[-0.63, 1.531, 1.06, 1.175, 0.329, 0.727], [0.734, 1.578, 0.984, 1.15, 0.266, 0.361]] C: [[-0.726, 1.106, 1.434, 1.522, 0.658, 0.308], [1.201, 1.481, 1.246, 0.828, 0.067, 0.371]] D: [[-0.719, 1.086, 1.264, 0.78, 0.793, 0.35], [0.868, 1.98, 0.75, 1.049, 0.201, 0.363]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_60_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_60_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.288, 3.663, 0.885, 1.742, 0.266, 1.508], [-1.19, -3.017, 0.715, 0.179, 0.346, 1.183], [-2.568, -0.991, 0.862, 0.362, 2.842, 1.652], [-2.356, 0.313, 1.087, 0.573, 0.323, 1.151], [-2.078, 0.891, 0.947, 0.102, 1.17, 1.498]] B: [[1.699, 3.879, 0.807, 1.466, 0.26, 1.658], [-1.338, -3.016, 0.481, -0.091, 0.125, 1.346], [-2.791, -0.651, 0.722, 0.588, 2.782, 1.444], [-2.133, -0.174, 1.179, 0.831, 0.459, 1.476], [-2.564, 1.303, 0.485, 0.444, 1.6, 1.79]] C: [[1.384, 3.837, 1.191, 2.116, 0.64, 1.217], [-1.185, -3.083, 1.042, 0.674, 0.205, 0.788], [-2.424, -0.728, 0.743, -0.005, 2.436, 1.937], [-2.645, -0.046, 0.933, 0.095, 0.125, 1.323], [-2.483, 0.961, 0.887, 0.154, 0.979, 1.595]] D: [[1.755, 3.461, 0.788, 1.786, 0.256, 1.208], [-1.596, -3.184, 0.789, 0.372, -0.041, 1.319], [-2.923, -1.052, 1.266, 0.216, 3.322, 1.837], [-2.525, 0.237, 1.346, 0.938, 0.473, 0.759], [-2.569, 1.257, 0.568, 0.003, 1.424, 1.337]]
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: [[-0.963317, 0.154363, -0.219528], [0.260086, 0.335369, -0.905474], [-0.066149, -0.929355, -0.363214]]; the translation vector: [5.972451, 2.818726, 1.468896], 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: [[1.288, 3.663, 0.885, 1.742, 0.266, 1.508], [-1.19, -3.017, 0.715, 0.179, 0.346, 1.183], [-2.568, -0.991, 0.862, 0.362, 2.842, 1.652], [-2.356, 0.313, 1.087, 0.573, 0.323, 1.151], [-2.078, 0.891, 0.947, 0.102, 1.17, 1.498]] B: [[1.699, 3.879, 0.807, 1.466, 0.26, 1.658], [-1.338, -3.016, 0.481, -0.091, 0.125, 1.346], [-2.791, -0.651, 0.722, 0.588, 2.782, 1.444], [-2.133, -0.174, 1.179, 0.831, 0.459, 1.476], [-2.564, 1.303, 0.485, 0.444, 1.6, 1.79]] C: [[1.384, 3.837, 1.191, 2.116, 0.64, 1.217], [-1.185, -3.083, 1.042, 0.674, 0.205, 0.788], [-2.424, -0.728, 0.743, -0.005, 2.436, 1.937], [-2.645, -0.046, 0.933, 0.095, 0.125, 1.323], [-2.483, 0.961, 0.887, 0.154, 0.979, 1.595]] D: [[1.755, 3.461, 0.788, 1.786, 0.256, 1.208], [-1.596, -3.184, 0.789, 0.372, -0.041, 1.319], [-2.923, -1.052, 1.266, 0.216, 3.322, 1.837], [-2.525, 0.237, 1.346, 0.938, 0.473, 0.759], [-2.569, 1.257, 0.568, 0.003, 1.424, 1.337]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_61_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_61_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.195, 2.616, 0.764, 0.381, 0.904, 1.179], [1.178, 2.791, 1.06, 0.523, 1.876, 0.795], [2.137, -1.926, -0.065, 1.185, 1.084, 0.312], [-0.599, -1.923, 0.519, 0.294, 0.992, 1.206]] B: [[-1.068, 2.261, 1.292, 0.971, 1.029, 0.824], [1.489, 3.189, 0.594, 0.774, 1.161, 1.156], [1.843, -2.018, 0.792, 0.473, 1.372, 0.616], [-0.424, -2.012, 0.649, 0.681, 1.809, 0.928]] C: [[-0.884, 2.735, 0.809, 0.721, 1.274, 0.906], [1.496, 2.941, 0.628, 0.833, 1.571, 0.871], [1.868, -1.949, 0.395, 0.878, 0.892, 0.788], [-0.793, -2.3, 0.359, 0.741, 1.335, 0.757]] D: [[-1.225, 2.279, 0.349, 0.295, 0.789, 0.542], [1.131, 2.464, 0.4, 0.503, 1.911, 0.903], [1.57, -1.598, -0.016, 1.245, 1.391, 0.466], [-0.41, -2.691, 0.26, 1.21, 1.681, 0.98]]
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: [[-0.824719, -0.175736, 0.537546], [-0.564369, 0.316962, -0.762249], [-0.036427, -0.932015, -0.360584]]; the translation vector: [4.397487, 4.054199, 1.411764], 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: [[-1.195, 2.616, 0.764, 0.381, 0.904, 1.179], [1.178, 2.791, 1.06, 0.523, 1.876, 0.795], [2.137, -1.926, -0.065, 1.185, 1.084, 0.312], [-0.599, -1.923, 0.519, 0.294, 0.992, 1.206]] B: [[-1.068, 2.261, 1.292, 0.971, 1.029, 0.824], [1.489, 3.189, 0.594, 0.774, 1.161, 1.156], [1.843, -2.018, 0.792, 0.473, 1.372, 0.616], [-0.424, -2.012, 0.649, 0.681, 1.809, 0.928]] C: [[-0.884, 2.735, 0.809, 0.721, 1.274, 0.906], [1.496, 2.941, 0.628, 0.833, 1.571, 0.871], [1.868, -1.949, 0.395, 0.878, 0.892, 0.788], [-0.793, -2.3, 0.359, 0.741, 1.335, 0.757]] D: [[-1.225, 2.279, 0.349, 0.295, 0.789, 0.542], [1.131, 2.464, 0.4, 0.503, 1.911, 0.903], [1.57, -1.598, -0.016, 1.245, 1.391, 0.466], [-0.41, -2.691, 0.26, 1.21, 1.681, 0.98]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_62_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_62_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.115, -1.562, 0.911, 0.99, 0.176, 0.93], [0.903, -1.409, 1.128, 0.969, 0.316, 0.989]] B: [[0.419, -1.51, 1.351, 0.838, 0.104, 1.371], [0.797, -1.27, 0.95, 0.885, 0.56, 0.709]] C: [[-0.056, -1.325, 0.584, 1.397, 0.105, 0.436], [0.94, -1.633, 1.178, 0.648, 0.434, 1.044]] D: [[0.609, -1.088, 0.429, 1.463, 0.186, 0.54], [0.51, -1.323, 0.699, 1.115, 0.814, 1.432]]
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: [[0.993805, -0.057016, 0.095394], [-0.110597, -0.423109, 0.899304], [-0.010913, -0.904283, -0.426794]]; the translation vector: [3.282054, 2.568905, 1.512321], 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: [[0.115, -1.562, 0.911, 0.99, 0.176, 0.93], [0.903, -1.409, 1.128, 0.969, 0.316, 0.989]] B: [[0.419, -1.51, 1.351, 0.838, 0.104, 1.371], [0.797, -1.27, 0.95, 0.885, 0.56, 0.709]] C: [[-0.056, -1.325, 0.584, 1.397, 0.105, 0.436], [0.94, -1.633, 1.178, 0.648, 0.434, 1.044]] D: [[0.609, -1.088, 0.429, 1.463, 0.186, 0.54], [0.51, -1.323, 0.699, 1.115, 0.814, 1.432]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_63_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_63_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.753, 0.465, 1.403, 0.46, 4.996, 2.959], [-1.738, -1.218, 1.272, 1.062, 1.528, 2.501], [-0.405, 2.797, 1.433, 4.292, 0.332, 2.875], [-2.525, 2.379, 1.355, 0.074, 0.839, 1.664], [-2.109, 0.693, 1.971, 0.227, 2.364, 1.533], [0.282, -2.054, 1.197, 3.118, 0.28, 2.272], [0.151, -2.857, 1.262, 0.294, 1.776, 2.355]] B: [[1.644, 0.604, 1.06, 0.766, 5.332, 3.344], [-2.097, -1.683, 0.861, 1.264, 1.832, 2.762], [-0.249, 2.988, 1.171, 4.734, 0.777, 3.234], [-2.915, 2.214, 1.5, 0.285, 1.098, 1.997], [-1.7, 0.54, 1.692, 0.479, 2.794, 1.178], [0.193, -1.942, 1.679, 3.173, -0.143, 2.182], [0.278, -3.151, 1.749, -0.197, 1.898, 2.594]] C: [[1.329, 0.268, 1.849, 0.784, 4.719, 2.961], [-2.126, -1.458, 1.073, 0.788, 1.484, 2.789], [0.005, 2.714, 1.367, 3.948, 0.242, 2.522], [-2.545, 2.463, 1.604, 0.21, 1.144, 1.521], [-1.811, 0.332, 2.299, -0.123, 1.943, 1.085], [0.387, -2.373, 0.727, 2.861, -0.215, 2.059], [0.369, -3.057, 1.007, 0.316, 1.439, 1.965]] D: [[2.224, 0.601, 1.81, 0.297, 5.34, 2.544], [-1.441, -1.038, 1.648, 1.209, 1.768, 2.642], [-0.455, 2.785, 1.909, 4.119, 0.083, 3.179], [-2.32, 2.048, 1.417, -0.178, 0.398, 1.998], [-1.992, 0.619, 1.973, 0.251, 2.119, 1.3], [0.593, -1.72, 1.138, 2.733, 0.423, 2.378], [0.595, -2.424, 1.148, 0.122, 2.12, 2.512]]
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: [[0.994136, 0.036629, -0.101745], [0.107123, -0.462198, 0.880283], [-0.014782, -0.88602, -0.463411]]; the translation vector: [3.8191, 1.340951, 1.354002], 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: [[1.753, 0.465, 1.403, 0.46, 4.996, 2.959], [-1.738, -1.218, 1.272, 1.062, 1.528, 2.501], [-0.405, 2.797, 1.433, 4.292, 0.332, 2.875], [-2.525, 2.379, 1.355, 0.074, 0.839, 1.664], [-2.109, 0.693, 1.971, 0.227, 2.364, 1.533], [0.282, -2.054, 1.197, 3.118, 0.28, 2.272], [0.151, -2.857, 1.262, 0.294, 1.776, 2.355]] B: [[1.644, 0.604, 1.06, 0.766, 5.332, 3.344], [-2.097, -1.683, 0.861, 1.264, 1.832, 2.762], [-0.249, 2.988, 1.171, 4.734, 0.777, 3.234], [-2.915, 2.214, 1.5, 0.285, 1.098, 1.997], [-1.7, 0.54, 1.692, 0.479, 2.794, 1.178], [0.193, -1.942, 1.679, 3.173, -0.143, 2.182], [0.278, -3.151, 1.749, -0.197, 1.898, 2.594]] C: [[1.329, 0.268, 1.849, 0.784, 4.719, 2.961], [-2.126, -1.458, 1.073, 0.788, 1.484, 2.789], [0.005, 2.714, 1.367, 3.948, 0.242, 2.522], [-2.545, 2.463, 1.604, 0.21, 1.144, 1.521], [-1.811, 0.332, 2.299, -0.123, 1.943, 1.085], [0.387, -2.373, 0.727, 2.861, -0.215, 2.059], [0.369, -3.057, 1.007, 0.316, 1.439, 1.965]] D: [[2.224, 0.601, 1.81, 0.297, 5.34, 2.544], [-1.441, -1.038, 1.648, 1.209, 1.768, 2.642], [-0.455, 2.785, 1.909, 4.119, 0.083, 3.179], [-2.32, 2.048, 1.417, -0.178, 0.398, 1.998], [-1.992, 0.619, 1.973, 0.251, 2.119, 1.3], [0.593, -1.72, 1.138, 2.733, 0.423, 2.378], [0.595, -2.424, 1.148, 0.122, 2.12, 2.512]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_64_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_64_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.229, -0.625, 1.789, 0.384, 0.619, 0.577], [-0.619, -2.375, 0.661, 0.567, 0.451, 0.111], [1.272, -2.43, 0.132, 0.447, 0.727, 0.3], [1.644, -2.684, 0.788, 0.577, 0.322, 0.308], [-0.576, -2.651, 0.078, 0.434, 0.523, 0.246], [0.194, -2.629, 0.081, 0.411, 0.494, 0.232], [0.495, -2.465, 0.021, 0.42, 0.459, 0.089], [-0.19, -2.648, 0.019, 0.384, 0.512, 0.116], [0.653, -2.701, 0.729, 0.282, 0.339, 0.17], [0.952, -2.696, 0.744, 0.349, 0.322, 0.22], [1.255, -2.766, 0.79, 0.368, 0.486, 0.32], [0.1, -2.746, 0.715, 0.314, 0.34, 0.156], [0.399, -2.748, 0.688, 0.296, 0.348, 0.103], [-0.127, -2.741, 0.687, 0.255, 0.368, 0.104], [-0.41, -2.745, 0.703, 0.341, 0.369, 0.132], [-1.782, -2.695, 0.512, 0.572, 0.485, 0.241], [-1.365, -2.686, 0.5, 0.492, 0.488, 0.277], [-1.027, -2.616, 0.39, 0.417, 0.378, 0.292], [-2.221, -0.682, 1.308, 0.347, 0.518, 0.497]] B: [[-2.177, -0.167, 1.791, 0.429, 0.305, 0.461], [-0.533, -2.428, 0.376, 0.625, 0.83, -0.181], [0.833, -2.571, -0.115, 0.273, 1.148, 0.126], [1.611, -2.253, 0.787, 0.359, 0.551, -0.134], [-1.058, -2.229, -0.315, 0.638, 0.268, -0.067], [0.333, -2.804, -0.071, 0.337, 0.161, 0.002], [0.886, -2.763, 0.464, 0.54, 0.824, 0.171], [0.083, -2.871, 0.059, 0.444, 0.352, 0.054], [0.665, -2.763, 0.558, 0.057, 0.308, 0.039], [0.563, -2.607, 1.101, 0.044, -0.169, 0.664], [1.085, -2.593, 0.464, 0.42, 0.951, 0.013], [-0.365, -2.365, 0.619, 0.59, 0.077, 0.369], [0.543, -2.864, 0.581, 0.554, 0.644, -0.05], [0.36, -3.102, 0.746, 0.301, -0.13, -0.221], [-0.22, -2.771, 1.165, 0.154, 0.295, 0.195], [-1.434, -2.444, 0.547, 0.734, 0.246, -0.108], [-0.997, -2.269, 0.094, 0.441, 0.845, 0.283], [-1.137, -2.213, 0.312, 0.148, 0.309, 0.772], [-2.498, -0.603, 1.369, 0.752, 0.555, 0.615]] C: [[-2.33, -1.056, 1.723, -0.065, 0.432, 0.415], [-0.968, -1.986, 0.569, 0.909, 0.497, 0.486], [1.32, -2.346, -0.114, 0.554, 0.588, 0.715], [1.949, -3.024, 0.857, 1.07, 0.018, 0.558], [-0.719, -2.255, 0.515, 0.899, 0.995, 0.643], [0.265, -2.28, -0.308, 0.384, 0.12, 0.468], [0.651, -2.056, -0.288, 0.45, 0.167, 0.402], [-0.058, -2.555, -0.352, 0.064, 0.242, 0.36], [0.516, -2.537, 1.033, 0.148, 0.192, 0.352], [0.983, -2.457, 0.904, -0.004, -0.102, -0.046], [1.601, -2.407, 0.354, 0.85, 0.773, 0.225], [0.09, -3.129, 0.278, 0.778, 0.065, 0.089], [0.498, -3.096, 0.49, 0.127, 0.025, 0.421], [0.282, -2.893, 0.585, 0.538, -0.078, 0.192], [-0.775, -2.875, 0.541, 0.822, 0.042, 0.614], [-1.444, -2.829, 0.956, 0.56, 0.015, 0.186], [-1.857, -2.941, 0.896, 0.404, 0.313, 0.437], [-1.23, -2.427, -0.01, 0.121, 0.029, 0.052], [-2.105, -0.861, 1.621, 0.843, 0.939, 0.137]] D: [[-2.187, -0.629, 2.131, 0.702, 0.488, 0.299], [-1.084, -2.454, 0.389, 0.263, 0.376, -0.0], [0.958, -2.794, -0.355, 0.189, 0.618, 0.078], [2.015, -2.977, 0.616, 0.785, -0.119, 0.807], [-0.732, -2.52, -0.405, 0.133, 0.556, -0.136], [0.099, -2.242, 0.21, 0.448, 0.703, 0.555], [0.296, -2.758, -0.175, 0.146, 0.559, 0.119], [0.107, -2.903, 0.259, 0.508, 0.683, 0.189], [0.807, -2.213, 0.988, -0.022, 0.827, 0.39], [1.137, -2.436, 0.849, 0.615, -0.156, -0.078], [1.291, -2.816, 0.462, 0.333, 0.002, 0.188], [-0.057, -2.486, 0.271, 0.707, 0.496, -0.343], [0.312, -2.462, 0.382, 0.486, 0.393, -0.299], [-0.367, -3.213, 1.027, 0.397, 0.32, -0.33], [-0.12, -2.591, 0.295, 0.767, -0.13, -0.295], [-1.934, -2.605, 0.653, 0.958, 0.354, 0.257], [-1.101, -2.538, 0.202, 0.148, 0.769, 0.141], [-0.928, -2.714, 0.387, 0.917, 0.787, 0.443], [-1.94, -0.799, 1.262, 0.381, 0.02, 0.723]]
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: [[0.983299, 0.047874, -0.175588], [0.180439, -0.382417, 0.9062], [-0.023764, -0.922749, -0.384668]]; the translation vector: [2.208684, 3.483128, 1.468268], 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: [[-2.229, -0.625, 1.789, 0.384, 0.619, 0.577], [-0.619, -2.375, 0.661, 0.567, 0.451, 0.111], [1.272, -2.43, 0.132, 0.447, 0.727, 0.3], [1.644, -2.684, 0.788, 0.577, 0.322, 0.308], [-0.576, -2.651, 0.078, 0.434, 0.523, 0.246], [0.194, -2.629, 0.081, 0.411, 0.494, 0.232], [0.495, -2.465, 0.021, 0.42, 0.459, 0.089], [-0.19, -2.648, 0.019, 0.384, 0.512, 0.116], [0.653, -2.701, 0.729, 0.282, 0.339, 0.17], [0.952, -2.696, 0.744, 0.349, 0.322, 0.22], [1.255, -2.766, 0.79, 0.368, 0.486, 0.32], [0.1, -2.746, 0.715, 0.314, 0.34, 0.156], [0.399, -2.748, 0.688, 0.296, 0.348, 0.103], [-0.127, -2.741, 0.687, 0.255, 0.368, 0.104], [-0.41, -2.745, 0.703, 0.341, 0.369, 0.132], [-1.782, -2.695, 0.512, 0.572, 0.485, 0.241], [-1.365, -2.686, 0.5, 0.492, 0.488, 0.277], [-1.027, -2.616, 0.39, 0.417, 0.378, 0.292], [-2.221, -0.682, 1.308, 0.347, 0.518, 0.497]] B: [[-2.177, -0.167, 1.791, 0.429, 0.305, 0.461], [-0.533, -2.428, 0.376, 0.625, 0.83, -0.181], [0.833, -2.571, -0.115, 0.273, 1.148, 0.126], [1.611, -2.253, 0.787, 0.359, 0.551, -0.134], [-1.058, -2.229, -0.315, 0.638, 0.268, -0.067], [0.333, -2.804, -0.071, 0.337, 0.161, 0.002], [0.886, -2.763, 0.464, 0.54, 0.824, 0.171], [0.083, -2.871, 0.059, 0.444, 0.352, 0.054], [0.665, -2.763, 0.558, 0.057, 0.308, 0.039], [0.563, -2.607, 1.101, 0.044, -0.169, 0.664], [1.085, -2.593, 0.464, 0.42, 0.951, 0.013], [-0.365, -2.365, 0.619, 0.59, 0.077, 0.369], [0.543, -2.864, 0.581, 0.554, 0.644, -0.05], [0.36, -3.102, 0.746, 0.301, -0.13, -0.221], [-0.22, -2.771, 1.165, 0.154, 0.295, 0.195], [-1.434, -2.444, 0.547, 0.734, 0.246, -0.108], [-0.997, -2.269, 0.094, 0.441, 0.845, 0.283], [-1.137, -2.213, 0.312, 0.148, 0.309, 0.772], [-2.498, -0.603, 1.369, 0.752, 0.555, 0.615]] C: [[-2.33, -1.056, 1.723, -0.065, 0.432, 0.415], [-0.968, -1.986, 0.569, 0.909, 0.497, 0.486], [1.32, -2.346, -0.114, 0.554, 0.588, 0.715], [1.949, -3.024, 0.857, 1.07, 0.018, 0.558], [-0.719, -2.255, 0.515, 0.899, 0.995, 0.643], [0.265, -2.28, -0.308, 0.384, 0.12, 0.468], [0.651, -2.056, -0.288, 0.45, 0.167, 0.402], [-0.058, -2.555, -0.352, 0.064, 0.242, 0.36], [0.516, -2.537, 1.033, 0.148, 0.192, 0.352], [0.983, -2.457, 0.904, -0.004, -0.102, -0.046], [1.601, -2.407, 0.354, 0.85, 0.773, 0.225], [0.09, -3.129, 0.278, 0.778, 0.065, 0.089], [0.498, -3.096, 0.49, 0.127, 0.025, 0.421], [0.282, -2.893, 0.585, 0.538, -0.078, 0.192], [-0.775, -2.875, 0.541, 0.822, 0.042, 0.614], [-1.444, -2.829, 0.956, 0.56, 0.015, 0.186], [-1.857, -2.941, 0.896, 0.404, 0.313, 0.437], [-1.23, -2.427, -0.01, 0.121, 0.029, 0.052], [-2.105, -0.861, 1.621, 0.843, 0.939, 0.137]] D: [[-2.187, -0.629, 2.131, 0.702, 0.488, 0.299], [-1.084, -2.454, 0.389, 0.263, 0.376, -0.0], [0.958, -2.794, -0.355, 0.189, 0.618, 0.078], [2.015, -2.977, 0.616, 0.785, -0.119, 0.807], [-0.732, -2.52, -0.405, 0.133, 0.556, -0.136], [0.099, -2.242, 0.21, 0.448, 0.703, 0.555], [0.296, -2.758, -0.175, 0.146, 0.559, 0.119], [0.107, -2.903, 0.259, 0.508, 0.683, 0.189], [0.807, -2.213, 0.988, -0.022, 0.827, 0.39], [1.137, -2.436, 0.849, 0.615, -0.156, -0.078], [1.291, -2.816, 0.462, 0.333, 0.002, 0.188], [-0.057, -2.486, 0.271, 0.707, 0.496, -0.343], [0.312, -2.462, 0.382, 0.486, 0.393, -0.299], [-0.367, -3.213, 1.027, 0.397, 0.32, -0.33], [-0.12, -2.591, 0.295, 0.767, -0.13, -0.295], [-1.934, -2.605, 0.653, 0.958, 0.354, 0.257], [-1.101, -2.538, 0.202, 0.148, 0.769, 0.141], [-0.928, -2.714, 0.387, 0.917, 0.787, 0.443], [-1.94, -0.799, 1.262, 0.381, 0.02, 0.723]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_65_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_65_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.897, 0.522, 0.459, 3.876, 6.999, 0.483]] B: [[-1.103, 0.265, -0.086, 3.353, 6.924, 0.299]] C: [[-1.473, 0.764, 0.085, 3.499, 6.843, 0.726]] D: [[-1.038, 0.389, 0.109, 3.778, 6.648, 0.286]]
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: [[0.643628, -0.362528, 0.674031], [-0.765241, -0.290748, 0.574345], [-0.012243, -0.88546, -0.464555]]; the translation vector: [2.632762, 2.243425, 1.452714], 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: [[-0.897, 0.522, 0.459, 3.876, 6.999, 0.483]] B: [[-1.103, 0.265, -0.086, 3.353, 6.924, 0.299]] C: [[-1.473, 0.764, 0.085, 3.499, 6.843, 0.726]] D: [[-1.038, 0.389, 0.109, 3.778, 6.648, 0.286]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_66_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_66_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.591, 1.483, 1.058, 1.607, 0.601, 2.492], [-2.097, -1.408, 0.835, 0.5, 0.336, 2.389]] B: [[0.134, 2.153, 0.957, 1.663, 0.233, 2.443], [-2.254, -1.53, 0.609, 0.554, 0.988, 1.584]] C: [[-0.108, 1.926, 1.025, 1.195, 0.255, 2.095], [-1.989, -1.419, 0.985, 0.159, 0.822, 1.991]] D: [[0.21, 1.976, 1.369, 1.051, 0.491, 1.606], [-2.131, -1.497, 0.9, 0.432, 0.96, 1.514]]
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: [[-0.925351, 0.122106, -0.358909], [0.376741, 0.190476, -0.906524], [-0.042329, -0.974068, -0.222259]]; the translation vector: [4.735593, 2.732706, 1.21643], 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: [[-0.591, 1.483, 1.058, 1.607, 0.601, 2.492], [-2.097, -1.408, 0.835, 0.5, 0.336, 2.389]] B: [[0.134, 2.153, 0.957, 1.663, 0.233, 2.443], [-2.254, -1.53, 0.609, 0.554, 0.988, 1.584]] C: [[-0.108, 1.926, 1.025, 1.195, 0.255, 2.095], [-1.989, -1.419, 0.985, 0.159, 0.822, 1.991]] D: [[0.21, 1.976, 1.369, 1.051, 0.491, 1.606], [-2.131, -1.497, 0.9, 0.432, 0.96, 1.514]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_67_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_67_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.347, 0.112, 0.25, 1.296, 0.747, 0.377], [-0.83, 0.341, 0.317, 1.198, 1.401, 0.615], [-0.794, -1.292, 0.479, 1.485, 1.035, 1.271], [0.127, 1.653, 0.718, 0.98, 0.518, 0.445]] B: [[1.529, 0.501, 0.301, 0.944, 1.585, 0.652], [-1.117, 0.064, 0.625, 0.722, 0.832, 1.296], [-1.406, -0.586, 0.491, 0.928, 1.591, 0.802], [0.516, 1.562, 0.345, 0.823, 1.417, 0.468]] C: [[1.382, -0.298, 0.162, 0.586, 1.271, 1.153], [-1.729, -0.043, 0.911, 1.507, 1.118, 1.281], [-0.888, -0.525, -0.057, 1.572, 1.192, 0.468], [-0.205, 1.524, 0.606, 0.689, 0.914, 0.382]] D: [[1.322, 0.194, 0.453, 1.016, 1.117, 0.863], [-1.253, 0.172, 0.421, 1.029, 1.045, 0.876], [-1.049, -0.979, 0.44, 1.12, 1.131, 0.861], [0.221, 1.294, 0.424, 0.876, 0.92, 0.832]]
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: [[0.748873, -0.374013, 0.547087], [-0.662404, -0.447673, 0.600675], [0.020256, -0.812221, -0.582998]]; the translation vector: [3.709567, 4.406117, 1.261793], 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: [[1.347, 0.112, 0.25, 1.296, 0.747, 0.377], [-0.83, 0.341, 0.317, 1.198, 1.401, 0.615], [-0.794, -1.292, 0.479, 1.485, 1.035, 1.271], [0.127, 1.653, 0.718, 0.98, 0.518, 0.445]] B: [[1.529, 0.501, 0.301, 0.944, 1.585, 0.652], [-1.117, 0.064, 0.625, 0.722, 0.832, 1.296], [-1.406, -0.586, 0.491, 0.928, 1.591, 0.802], [0.516, 1.562, 0.345, 0.823, 1.417, 0.468]] C: [[1.382, -0.298, 0.162, 0.586, 1.271, 1.153], [-1.729, -0.043, 0.911, 1.507, 1.118, 1.281], [-0.888, -0.525, -0.057, 1.572, 1.192, 0.468], [-0.205, 1.524, 0.606, 0.689, 0.914, 0.382]] D: [[1.322, 0.194, 0.453, 1.016, 1.117, 0.863], [-1.253, 0.172, 0.421, 1.029, 1.045, 0.876], [-1.049, -0.979, 0.44, 1.12, 1.131, 0.861], [0.221, 1.294, 0.424, 0.876, 0.92, 0.832]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_68_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_68_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.579, -0.488, 0.759, 0.356, 0.729, 0.206], [-1.432, 0.41, 0.224, 0.816, -0.16, 0.054], [-1.128, 1.211, 0.876, 0.072, 0.472, -0.431], [-0.056, 1.335, 1.059, 0.219, -0.158, 0.294], [0.39, 0.373, 0.895, 0.659, 0.538, 0.377], [-1.237, 2.65, 0.314, 0.655, 0.335, -0.177]] B: [[-1.898, -0.166, 1.244, 0.693, 0.01, 0.135], [-2.054, 0.428, 0.961, 0.919, 0.356, 0.407], [-1.294, 1.065, 0.511, 0.811, -0.08, -0.323], [0.085, 0.558, 1.04, 0.703, -0.22, -0.384], [1.147, 0.956, 0.305, 0.157, 0.461, -0.367], [-1.796, 2.739, 0.408, 0.015, 0.305, -0.245]] C: [[-1.472, -0.634, 0.769, 0.41, 0.312, 0.075], [-1.766, 0.861, 0.684, 0.449, 0.16, 0.051], [-0.868, 0.879, 0.668, 0.414, 0.211, 0.046], [-0.148, 0.874, 0.644, 0.427, 0.151, 0.056], [0.744, 0.838, 0.607, 0.528, 0.174, 0.072], [-1.369, 2.612, 0.558, 0.426, 0.186, 0.029]] D: [[-1.326, -0.492, 0.759, 0.773, 0.113, -0.399], [-1.742, 0.884, 0.249, 0.825, 0.051, -0.219], [-0.59, 0.654, 0.814, 0.491, -0.041, -0.171], [-0.618, 1.322, 0.366, 0.807, 0.377, 0.225], [1.165, 1.152, 0.365, 0.032, 0.059, 0.012], [-1.206, 2.669, 0.552, 0.305, 0.052, 0.19]]
Given a RGB image and a depth image, please detect the 3D bounding box of the keyboard in the scene. The camera pose information includes: the rotation matrix: [[0.053762, 0.423971, -0.904079], [0.99709, -0.071809, 0.025618], [-0.05406, -0.902825, -0.426597]]; the translation vector: [3.696534, 7.381392, 1.65485], 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: [[-1.579, -0.488, 0.759, 0.356, 0.729, 0.206], [-1.432, 0.41, 0.224, 0.816, -0.16, 0.054], [-1.128, 1.211, 0.876, 0.072, 0.472, -0.431], [-0.056, 1.335, 1.059, 0.219, -0.158, 0.294], [0.39, 0.373, 0.895, 0.659, 0.538, 0.377], [-1.237, 2.65, 0.314, 0.655, 0.335, -0.177]] B: [[-1.898, -0.166, 1.244, 0.693, 0.01, 0.135], [-2.054, 0.428, 0.961, 0.919, 0.356, 0.407], [-1.294, 1.065, 0.511, 0.811, -0.08, -0.323], [0.085, 0.558, 1.04, 0.703, -0.22, -0.384], [1.147, 0.956, 0.305, 0.157, 0.461, -0.367], [-1.796, 2.739, 0.408, 0.015, 0.305, -0.245]] C: [[-1.472, -0.634, 0.769, 0.41, 0.312, 0.075], [-1.766, 0.861, 0.684, 0.449, 0.16, 0.051], [-0.868, 0.879, 0.668, 0.414, 0.211, 0.046], [-0.148, 0.874, 0.644, 0.427, 0.151, 0.056], [0.744, 0.838, 0.607, 0.528, 0.174, 0.072], [-1.369, 2.612, 0.558, 0.426, 0.186, 0.029]] D: [[-1.326, -0.492, 0.759, 0.773, 0.113, -0.399], [-1.742, 0.884, 0.249, 0.825, 0.051, -0.219], [-0.59, 0.654, 0.814, 0.491, -0.041, -0.171], [-0.618, 1.322, 0.366, 0.807, 0.377, 0.225], [1.165, 1.152, 0.365, 0.032, 0.059, 0.012], [-1.206, 2.669, 0.552, 0.305, 0.052, 0.19]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_69_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_69_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.062, 0.255, 0.974, 0.478, 0.305, 1.9]] B: [[0.289, 0.114, 0.997, 0.421, 0.269, 2.332]] C: [[-0.529, -0.167, 1.248, 0.711, 0.631, 1.869]] D: [[-0.117, 0.693, 1.129, 0.484, 0.656, 2.156]]
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: [[-0.95695, -0.100486, 0.272304], [-0.288986, 0.24231, -0.92616], [0.027085, -0.964981, -0.260918]]; the translation vector: [1.227478, 4.879099, 1.55452], 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: [[-0.062, 0.255, 0.974, 0.478, 0.305, 1.9]] B: [[0.289, 0.114, 0.997, 0.421, 0.269, 2.332]] C: [[-0.529, -0.167, 1.248, 0.711, 0.631, 1.869]] D: [[-0.117, 0.693, 1.129, 0.484, 0.656, 2.156]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_70_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_70_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.525, -2.231, 0.892, 0.349, 0.481, 0.091]] B: [[1.636, -2.317, 0.937, 0.292, 0.774, -0.26]] C: [[1.735, -2.218, 1.132, -0.039, 0.012, 0.228]] D: [[1.335, -2.53, 1.027, 0.634, 0.978, -0.278]]
Given a RGB image and a depth image, please detect the 3D bounding box of the book in the scene. The camera pose information includes: the rotation matrix: [[-0.863619, -0.252896, 0.436126], [-0.502889, 0.371124, -0.780621], [0.03556, -0.893482, -0.447688]]; the translation vector: [2.007098, 3.82416, 1.536992], 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: [[1.525, -2.231, 0.892, 0.349, 0.481, 0.091]] B: [[1.636, -2.317, 0.937, 0.292, 0.774, -0.26]] C: [[1.735, -2.218, 1.132, -0.039, 0.012, 0.228]] D: [[1.335, -2.53, 1.027, 0.634, 0.978, -0.278]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_71_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_71_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-3.713, -2.322, 1.093, 0.437, 3.072, 2.045], [-1.081, -3.837, 1.495, 4.867, 0.501, 2.558], [2.258, -2.553, 1.174, 1.342, 1.564, 2.568], [3.141, 1.147, 1.716, 0.254, 5.221, 3.492], [1.44, -2.565, 1.73, 0.493, 2.338, 2.511], [1.459, -1.994, 0.755, 0.967, 0.884, 1.183], [1.27, 3.225, 1.429, 3.362, 0.06, 2.461], [2.687, -1.112, 0.928, 2.314, 0.606, 3.137], [3.573, 2.12, 0.945, -0.323, 1.165, 0.653]] B: [[-3.835, -1.629, 1.168, -0.265, 2.747, 2.333], [-1.318, -2.989, 1.688, 4.412, 0.48, 2.388], [2.689, -2.933, 1.545, 1.676, 2.18, 2.201], [3.228, 1.403, 1.452, 0.635, 4.562, 3.257], [1.389, -2.608, 0.976, 1.337, 2.222, 2.449], [1.683, -1.57, 0.448, 0.488, 1.125, 1.219], [1.286, 3.78, 1.634, 2.717, 0.735, 2.673], [2.077, -1.004, 0.831, 1.778, 0.571, 2.523], [3.367, 1.994, 0.998, 0.165, 1.01, 0.878]] C: [[-3.518, -1.854, 1.546, 0.215, 3.24, 2.228], [-1.249, -3.369, 1.199, 4.514, 0.422, 2.472], [2.581, -2.461, 1.261, 1.576, 1.946, 2.535], [3.098, 1.012, 1.522, 0.435, 4.946, 2.999], [1.343, -2.44, 1.234, 0.869, 1.985, 2.527], [1.357, -2.033, 0.708, 0.777, 1.087, 1.434], [1.727, 3.433, 1.218, 3.174, 0.459, 2.415], [2.388, -1.448, 1.321, 1.857, 0.151, 2.689], [3.207, 2.39, 1.139, 0.116, 1.457, 0.447]] D: [[-3.315, -1.725, 1.076, -0.072, 3.369, 2.316], [-1.509, -2.948, 1.263, 4.588, 0.454, 2.009], [2.958, -2.942, 0.867, 1.911, 2.392, 2.127], [3.566, 0.671, 1.618, 0.253, 5.112, 3.1], [1.816, -2.011, 1.094, 0.402, 1.679, 2.148], [0.957, -1.668, 0.579, 1.105, 0.683, 1.586], [1.676, 3.716, 1.075, 3.204, 0.902, 2.406], [2.655, -1.717, 0.827, 1.883, 0.155, 2.358], [3.511, 2.562, 1.175, -0.348, 1.486, 0.553]]
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: [[-0.831143, 0.312948, -0.459636], [0.555586, 0.43327, -0.709649], [-0.022937, -0.845187, -0.533978]]; the translation vector: [2.360292, 3.05803, 1.315354], 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: [[-3.713, -2.322, 1.093, 0.437, 3.072, 2.045], [-1.081, -3.837, 1.495, 4.867, 0.501, 2.558], [2.258, -2.553, 1.174, 1.342, 1.564, 2.568], [3.141, 1.147, 1.716, 0.254, 5.221, 3.492], [1.44, -2.565, 1.73, 0.493, 2.338, 2.511], [1.459, -1.994, 0.755, 0.967, 0.884, 1.183], [1.27, 3.225, 1.429, 3.362, 0.06, 2.461], [2.687, -1.112, 0.928, 2.314, 0.606, 3.137], [3.573, 2.12, 0.945, -0.323, 1.165, 0.653]] B: [[-3.835, -1.629, 1.168, -0.265, 2.747, 2.333], [-1.318, -2.989, 1.688, 4.412, 0.48, 2.388], [2.689, -2.933, 1.545, 1.676, 2.18, 2.201], [3.228, 1.403, 1.452, 0.635, 4.562, 3.257], [1.389, -2.608, 0.976, 1.337, 2.222, 2.449], [1.683, -1.57, 0.448, 0.488, 1.125, 1.219], [1.286, 3.78, 1.634, 2.717, 0.735, 2.673], [2.077, -1.004, 0.831, 1.778, 0.571, 2.523], [3.367, 1.994, 0.998, 0.165, 1.01, 0.878]] C: [[-3.518, -1.854, 1.546, 0.215, 3.24, 2.228], [-1.249, -3.369, 1.199, 4.514, 0.422, 2.472], [2.581, -2.461, 1.261, 1.576, 1.946, 2.535], [3.098, 1.012, 1.522, 0.435, 4.946, 2.999], [1.343, -2.44, 1.234, 0.869, 1.985, 2.527], [1.357, -2.033, 0.708, 0.777, 1.087, 1.434], [1.727, 3.433, 1.218, 3.174, 0.459, 2.415], [2.388, -1.448, 1.321, 1.857, 0.151, 2.689], [3.207, 2.39, 1.139, 0.116, 1.457, 0.447]] D: [[-3.315, -1.725, 1.076, -0.072, 3.369, 2.316], [-1.509, -2.948, 1.263, 4.588, 0.454, 2.009], [2.958, -2.942, 0.867, 1.911, 2.392, 2.127], [3.566, 0.671, 1.618, 0.253, 5.112, 3.1], [1.816, -2.011, 1.094, 0.402, 1.679, 2.148], [0.957, -1.668, 0.579, 1.105, 0.683, 1.586], [1.676, 3.716, 1.075, 3.204, 0.902, 2.406], [2.655, -1.717, 0.827, 1.883, 0.155, 2.358], [3.511, 2.562, 1.175, -0.348, 1.486, 0.553]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_72_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_72_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.046, -0.307, 0.362, 0.784, -0.024, 0.785], [1.165, -2.351, 1.138, 0.213, 0.736, 0.353], [1.15, -2.093, 0.722, 0.4, 0.33, 0.205], [1.084, -0.85, 1.131, 0.451, -0.085, 0.317], [1.331, -1.435, 0.691, 0.675, 0.723, 0.254], [-1.236, 0.563, -0.088, 0.27, -0.102, 0.794]] B: [[1.265, -0.056, 0.282, 0.326, 0.027, 0.886], [1.533, -2.203, 0.449, 0.341, 0.914, 0.835], [0.973, -1.818, 0.452, -0.205, -0.0, 0.557], [1.212, -0.809, 0.364, 0.233, 0.14, 0.279], [0.952, -0.74, 0.435, -0.133, 0.174, 0.554], [-1.162, 0.16, 0.691, 0.327, -0.202, 0.736]] C: [[1.057, -0.394, 0.235, 0.507, 0.4, 0.47], [1.152, -1.942, 0.923, 0.249, 0.43, 0.441], [1.185, -1.67, 0.793, 0.195, 0.105, 0.183], [0.815, -0.905, 0.823, 0.231, 0.165, 0.244], [0.988, -0.991, 0.818, 0.253, 0.25, 0.209], [-1.265, 0.61, 0.238, 0.204, 0.16, 0.435]] D: [[1.051, -0.65, -0.171, 0.578, 0.483, 0.109], [0.936, -1.859, 0.474, -0.087, 0.06, 0.148], [1.334, -2.107, 0.81, 0.465, 0.412, 0.633], [0.554, -0.966, 0.763, 0.354, 0.344, 0.116], [1.173, -0.543, 0.619, 0.486, 0.296, 0.039], [-1.019, 0.12, 0.267, -0.232, -0.155, 0.735]]
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: [[0.264492, -0.222038, 0.938479], [-0.962334, 0.002714, 0.271857], [-0.062909, -0.975034, -0.212957]]; the translation vector: [0.925816, 4.784833, 1.497389], 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: [[1.046, -0.307, 0.362, 0.784, -0.024, 0.785], [1.165, -2.351, 1.138, 0.213, 0.736, 0.353], [1.15, -2.093, 0.722, 0.4, 0.33, 0.205], [1.084, -0.85, 1.131, 0.451, -0.085, 0.317], [1.331, -1.435, 0.691, 0.675, 0.723, 0.254], [-1.236, 0.563, -0.088, 0.27, -0.102, 0.794]] B: [[1.265, -0.056, 0.282, 0.326, 0.027, 0.886], [1.533, -2.203, 0.449, 0.341, 0.914, 0.835], [0.973, -1.818, 0.452, -0.205, -0.0, 0.557], [1.212, -0.809, 0.364, 0.233, 0.14, 0.279], [0.952, -0.74, 0.435, -0.133, 0.174, 0.554], [-1.162, 0.16, 0.691, 0.327, -0.202, 0.736]] C: [[1.057, -0.394, 0.235, 0.507, 0.4, 0.47], [1.152, -1.942, 0.923, 0.249, 0.43, 0.441], [1.185, -1.67, 0.793, 0.195, 0.105, 0.183], [0.815, -0.905, 0.823, 0.231, 0.165, 0.244], [0.988, -0.991, 0.818, 0.253, 0.25, 0.209], [-1.265, 0.61, 0.238, 0.204, 0.16, 0.435]] D: [[1.051, -0.65, -0.171, 0.578, 0.483, 0.109], [0.936, -1.859, 0.474, -0.087, 0.06, 0.148], [1.334, -2.107, 0.81, 0.465, 0.412, 0.633], [0.554, -0.966, 0.763, 0.354, 0.344, 0.116], [1.173, -0.543, 0.619, 0.486, 0.296, 0.039], [-1.019, 0.12, 0.267, -0.232, -0.155, 0.735]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_73_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_73_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.085, -0.215, 0.983, 0.671, 0.944, 0.637]] B: [[-1.195, -0.19, 1.175, 0.471, 1.343, 0.221]] C: [[-1.17, -0.298, 0.934, 0.962, 1.213, 0.413]] D: [[-1.39, -0.221, 0.693, 0.182, 1.277, 0.167]]
Given a RGB image and a depth image, please detect the 3D bounding box of the sink in the scene. The camera pose information includes: the rotation matrix: [[-0.409087, -0.112571, 0.905525], [-0.910894, 0.109148, -0.397943], [-0.05404, -0.987631, -0.147191]]; the translation vector: [4.421403, 3.579741, 1.526424], 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: [[-1.085, -0.215, 0.983, 0.671, 0.944, 0.637]] B: [[-1.195, -0.19, 1.175, 0.471, 1.343, 0.221]] C: [[-1.17, -0.298, 0.934, 0.962, 1.213, 0.413]] D: [[-1.39, -0.221, 0.693, 0.182, 1.277, 0.167]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_74_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_74_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.095, 1.592, 1.222, 1.568, 0.744, 2.142]] B: [[-0.877, 2.359, 1.301, 1.758, 0.807, 2.272]] C: [[-0.883, 2.133, 0.636, 0.867, 0.763, 2.547]] D: [[-1.101, 1.96, 1.128, 1.33, 0.454, 2.075]]
Given a RGB image and a depth image, please detect the 3D bounding box of the mirror doors in the scene. The camera pose information includes: the rotation matrix: [[-0.998134, -0.025826, -0.055325], [0.04389, 0.326427, -0.944203], [0.042444, -0.94487, -0.324684]]; the translation vector: [2.355182, 2.984659, 1.395898], 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: [[-1.095, 1.592, 1.222, 1.568, 0.744, 2.142]] B: [[-0.877, 2.359, 1.301, 1.758, 0.807, 2.272]] C: [[-0.883, 2.133, 0.636, 0.867, 0.763, 2.547]] D: [[-1.101, 1.96, 1.128, 1.33, 0.454, 2.075]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_75_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_75_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.917, 0.769, 0.393, 0.162, 0.916, 0.83], [2.158, 0.091, 1.885, 0.64, 0.369, 0.373]] B: [[1.7, 0.645, 0.863, 0.067, 1.221, 0.849], [2.328, 0.352, 2.246, 0.627, 0.498, 0.253]] C: [[1.798, 1.202, -0.093, 0.135, 0.516, 1.131], [2.029, 0.523, 2.037, 0.813, 0.35, 0.6]] D: [[1.675, 0.61, 0.316, -0.227, 0.481, 0.35], [2.253, 0.494, 1.51, 1.013, 0.177, 0.842]]
Given a RGB image and a depth image, please detect the 3D bounding box of the kitchen cabinet in the scene. The camera pose information includes: the rotation matrix: [[-0.399387, 0.327689, -0.856218], [0.9115, 0.041819, -0.409169], [-0.098274, -0.94386, -0.315391]]; the translation vector: [4.88233, 2.963563, 1.403722], 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: [[1.917, 0.769, 0.393, 0.162, 0.916, 0.83], [2.158, 0.091, 1.885, 0.64, 0.369, 0.373]] B: [[1.7, 0.645, 0.863, 0.067, 1.221, 0.849], [2.328, 0.352, 2.246, 0.627, 0.498, 0.253]] C: [[1.798, 1.202, -0.093, 0.135, 0.516, 1.131], [2.029, 0.523, 2.037, 0.813, 0.35, 0.6]] D: [[1.675, 0.61, 0.316, -0.227, 0.481, 0.35], [2.253, 0.494, 1.51, 1.013, 0.177, 0.842]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_76_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_76_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.494, 1.559, 0.938, 0.656, 5.217, 2.076], [2.053, 1.519, 1.142, 0.022, 3.126, 1.696], [1.526, 0.314, 1.467, 0.388, 0.432, 1.965], [1.119, -0.324, 1.442, 0.427, 0.845, 2.198], [1.576, -0.035, 0.321, 0.045, 0.534, 1.117], [1.692, -0.958, 0.006, 0.205, 2.737, 0.651], [2.137, -2.631, 1.077, 0.184, 0.904, 1.508], [1.333, -3.255, 1.466, 0.791, -0.082, 1.662], [1.459, -3.425, 1.79, -0.348, -0.024, 0.359], [0.387, -3.416, 1.314, 3.646, -0.097, 1.995], [-1.825, -3.194, 1.168, 0.422, 1.404, 1.529], [-0.304, 4.179, 0.452, 3.264, -0.007, 1.066], [1.999, 3.872, 0.716, 0.498, 0.487, 1.358]] B: [[-1.693, 1.424, 1.03, 0.376, 5.083, 2.034], [1.765, 1.957, 1.138, 0.161, 3.199, 2.18], [1.589, 0.333, 0.987, 0.355, 0.095, 1.877], [1.425, 0.157, 1.015, 0.112, 0.477, 1.967], [1.63, -0.081, 0.672, 0.331, 0.259, 1.339], [1.705, -1.447, 0.484, 0.238, 2.779, 0.873], [1.951, -2.837, 1.012, 0.146, 0.69, 1.445], [1.797, -3.186, 1.022, 0.444, 0.092, 1.424], [1.591, -3.334, 1.384, 0.106, 0.324, 0.652], [-0.022, -3.519, 0.892, 3.311, 0.275, 1.699], [-1.705, -2.728, 0.676, 0.126, 1.402, 1.204], [-0.01, 3.839, 0.745, 3.147, 0.481, 1.347], [1.63, 3.568, 0.892, 0.411, 0.327, 1.532]] C: [[-1.26, 1.503, 0.893, 0.629, 5.544, 1.914], [2.175, 1.47, 1.47, 0.109, 3.382, 1.686], [1.982, -0.011, 0.916, 0.426, -0.326, 1.566], [1.181, 0.067, 1.21, 0.067, 0.005, 2.351], [1.524, 0.001, 0.471, 0.286, 0.408, 1.265], [1.238, -1.52, 0.419, 0.599, 3.184, 1.176], [1.553, -3.177, 0.653, 0.32, 0.427, 1.885], [1.383, -3.363, 1.432, 0.865, -0.009, 1.444], [1.288, -3.498, 1.769, -0.257, 0.218, 1.054], [0.393, -3.522, 1.337, 3.619, 0.242, 1.594], [-1.576, -3.113, 0.753, 0.379, 1.777, 1.195], [-0.268, 3.894, 0.852, 2.983, 0.721, 1.393], [1.465, 3.133, 0.435, 0.617, 0.63, 1.96]] D: [[-1.946, 1.454, 1.304, 0.285, 4.759, 1.584], [1.735, 2.118, 1.431, 0.5, 3.38, 2.198], [2.01, 0.269, 1.406, 0.118, -0.362, 2.255], [1.665, -0.294, 0.623, -0.295, 0.208, 2.363], [1.918, 0.112, 1.078, 0.599, 0.597, 0.896], [1.655, -1.698, 0.75, 0.063, 2.896, 0.441], [2.382, -2.981, 1.161, 0.203, 0.379, 1.162], [1.828, -2.97, 0.979, 0.706, -0.194, 1.801], [1.717, -3.159, 1.188, 0.204, 0.385, 0.448], [0.303, -3.389, 1.008, 3.649, 0.715, 1.331], [-1.467, -2.443, 0.641, 0.545, 0.903, 1.371], [-0.151, 3.761, 0.508, 3.288, 0.802, 1.225], [1.797, 3.579, 1.179, 0.009, 0.008, 1.708]]
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: [[-0.810147, -0.229725, 0.539341], [-0.586224, 0.314131, -0.746769], [0.002128, -0.921167, -0.389162]]; the translation vector: [3.108561, 2.950706, 1.466118], 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: [[-1.494, 1.559, 0.938, 0.656, 5.217, 2.076], [2.053, 1.519, 1.142, 0.022, 3.126, 1.696], [1.526, 0.314, 1.467, 0.388, 0.432, 1.965], [1.119, -0.324, 1.442, 0.427, 0.845, 2.198], [1.576, -0.035, 0.321, 0.045, 0.534, 1.117], [1.692, -0.958, 0.006, 0.205, 2.737, 0.651], [2.137, -2.631, 1.077, 0.184, 0.904, 1.508], [1.333, -3.255, 1.466, 0.791, -0.082, 1.662], [1.459, -3.425, 1.79, -0.348, -0.024, 0.359], [0.387, -3.416, 1.314, 3.646, -0.097, 1.995], [-1.825, -3.194, 1.168, 0.422, 1.404, 1.529], [-0.304, 4.179, 0.452, 3.264, -0.007, 1.066], [1.999, 3.872, 0.716, 0.498, 0.487, 1.358]] B: [[-1.693, 1.424, 1.03, 0.376, 5.083, 2.034], [1.765, 1.957, 1.138, 0.161, 3.199, 2.18], [1.589, 0.333, 0.987, 0.355, 0.095, 1.877], [1.425, 0.157, 1.015, 0.112, 0.477, 1.967], [1.63, -0.081, 0.672, 0.331, 0.259, 1.339], [1.705, -1.447, 0.484, 0.238, 2.779, 0.873], [1.951, -2.837, 1.012, 0.146, 0.69, 1.445], [1.797, -3.186, 1.022, 0.444, 0.092, 1.424], [1.591, -3.334, 1.384, 0.106, 0.324, 0.652], [-0.022, -3.519, 0.892, 3.311, 0.275, 1.699], [-1.705, -2.728, 0.676, 0.126, 1.402, 1.204], [-0.01, 3.839, 0.745, 3.147, 0.481, 1.347], [1.63, 3.568, 0.892, 0.411, 0.327, 1.532]] C: [[-1.26, 1.503, 0.893, 0.629, 5.544, 1.914], [2.175, 1.47, 1.47, 0.109, 3.382, 1.686], [1.982, -0.011, 0.916, 0.426, -0.326, 1.566], [1.181, 0.067, 1.21, 0.067, 0.005, 2.351], [1.524, 0.001, 0.471, 0.286, 0.408, 1.265], [1.238, -1.52, 0.419, 0.599, 3.184, 1.176], [1.553, -3.177, 0.653, 0.32, 0.427, 1.885], [1.383, -3.363, 1.432, 0.865, -0.009, 1.444], [1.288, -3.498, 1.769, -0.257, 0.218, 1.054], [0.393, -3.522, 1.337, 3.619, 0.242, 1.594], [-1.576, -3.113, 0.753, 0.379, 1.777, 1.195], [-0.268, 3.894, 0.852, 2.983, 0.721, 1.393], [1.465, 3.133, 0.435, 0.617, 0.63, 1.96]] D: [[-1.946, 1.454, 1.304, 0.285, 4.759, 1.584], [1.735, 2.118, 1.431, 0.5, 3.38, 2.198], [2.01, 0.269, 1.406, 0.118, -0.362, 2.255], [1.665, -0.294, 0.623, -0.295, 0.208, 2.363], [1.918, 0.112, 1.078, 0.599, 0.597, 0.896], [1.655, -1.698, 0.75, 0.063, 2.896, 0.441], [2.382, -2.981, 1.161, 0.203, 0.379, 1.162], [1.828, -2.97, 0.979, 0.706, -0.194, 1.801], [1.717, -3.159, 1.188, 0.204, 0.385, 0.448], [0.303, -3.389, 1.008, 3.649, 0.715, 1.331], [-1.467, -2.443, 0.641, 0.545, 0.903, 1.371], [-0.151, 3.761, 0.508, 3.288, 0.802, 1.225], [1.797, 3.579, 1.179, 0.009, 0.008, 1.708]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_77_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_77_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.793, 1.247, 0.29, 0.296, 0.279, -0.014], [1.019, 0.024, 1.569, 0.553, 0.236, 0.679]] B: [[-0.837, 1.73, 0.172, 0.311, 0.446, 0.446], [0.579, -0.45, 1.284, 0.394, 0.372, 0.858]] C: [[-0.983, 2.19, 0.493, -0.03, 0.329, 0.928], [0.864, -0.587, 1.773, 0.118, 0.794, 0.799]] D: [[-0.553, 2.216, 0.459, 0.267, 0.459, 0.522], [0.806, 0.026, 1.267, 0.403, 0.702, 0.558]]
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: [[-0.187285, -0.627824, 0.755488], [-0.982305, 0.118515, -0.145025], [0.001514, -0.76928, -0.63891]]; the translation vector: [1.001752, 1.17634, 1.437838], 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: [[-0.793, 1.247, 0.29, 0.296, 0.279, -0.014], [1.019, 0.024, 1.569, 0.553, 0.236, 0.679]] B: [[-0.837, 1.73, 0.172, 0.311, 0.446, 0.446], [0.579, -0.45, 1.284, 0.394, 0.372, 0.858]] C: [[-0.983, 2.19, 0.493, -0.03, 0.329, 0.928], [0.864, -0.587, 1.773, 0.118, 0.794, 0.799]] D: [[-0.553, 2.216, 0.459, 0.267, 0.459, 0.522], [0.806, 0.026, 1.267, 0.403, 0.702, 0.558]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_78_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_78_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.858, -1.05, -0.049, 0.631, 1.092, 1.022], [0.969, 2.457, 0.703, 0.33, 0.355, 0.535], [1.292, 0.687, 0.943, 0.724, 0.324, 1.126], [1.537, -0.024, 0.37, 0.738, 0.769, 0.806], [2.91, -1.195, 1.375, 0.242, 1.166, 0.582], [2.799, -1.708, 0.863, 0.877, 0.364, 0.812], [2.158, -1.992, 0.634, 0.411, 0.065, 1.19], [-2.861, 0.973, 1.098, 0.744, 0.232, 0.595], [-3.055, 1.702, 0.901, 0.639, 0.173, 0.718], [3.451, -0.934, 1.096, 0.502, 0.89, 0.387]] B: [[-2.77, -0.712, 0.41, 0.782, 0.713, 0.859], [1.367, 2.116, 0.842, 0.257, 0.504, 0.248], [1.716, 0.519, 0.519, 0.661, 0.573, 0.903], [1.577, -0.324, 0.811, 0.462, 0.54, 0.431], [3.037, -1.452, 0.953, 0.581, 0.687, 0.531], [2.669, -1.872, 0.986, 0.552, 0.48, 0.568], [2.211, -1.887, 0.725, 0.677, 0.554, 1.018], [-2.956, 0.672, 0.826, 0.436, 0.319, 0.465], [-2.626, 1.651, 0.53, 0.537, 0.47, 0.924], [2.995, -0.435, 0.615, 0.566, 0.706, 0.886]] C: [[-2.925, -0.243, 0.295, 0.519, 0.44, 0.711], [1.485, 1.766, 1.018, 0.081, 0.848, 0.483], [1.717, 0.68, 0.214, 0.236, 1.037, 0.434], [1.205, -0.323, 1.125, 0.097, 0.642, 0.242], [3.189, -1.068, 0.599, 0.36, 1.144, 0.939], [2.418, -1.941, 1.167, 0.598, 0.698, 0.702], [1.723, -2.159, 0.821, 0.484, 0.884, 0.696], [-3.03, 0.47, 1.025, 0.789, 0.045, 0.278], [-2.913, 1.461, 0.819, 0.202, 0.085, 1.03], [2.826, -0.221, 0.951, 0.339, 0.752, 1.266]] D: [[-3.135, -0.575, -0.082, 0.411, 0.399, 1.112], [1.76, 1.636, 0.661, -0.118, 0.316, 0.196], [2.067, 0.976, 0.67, 0.22, 0.315, 1.158], [1.439, -0.283, 0.584, 0.087, 0.218, 0.206], [2.848, -1.357, 1.295, 0.653, 0.266, 0.059], [2.99, -1.86, 1.333, 0.578, 0.108, 0.112], [2.118, -1.567, 1.178, 0.323, 0.289, 0.96], [-3.43, 1.005, 1.071, 0.331, 0.71, 0.959], [-3.114, 1.972, 0.571, 0.075, 0.864, 0.441], [2.987, 0.022, 0.923, 0.173, 0.274, 0.482]]
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: [[0.515401, -0.339121, 0.786994], [-0.847541, -0.337435, 0.40965], [0.126638, -0.878143, -0.461333]]; the translation vector: [4.776819, 1.138867, 1.280463], 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: [[-2.858, -1.05, -0.049, 0.631, 1.092, 1.022], [0.969, 2.457, 0.703, 0.33, 0.355, 0.535], [1.292, 0.687, 0.943, 0.724, 0.324, 1.126], [1.537, -0.024, 0.37, 0.738, 0.769, 0.806], [2.91, -1.195, 1.375, 0.242, 1.166, 0.582], [2.799, -1.708, 0.863, 0.877, 0.364, 0.812], [2.158, -1.992, 0.634, 0.411, 0.065, 1.19], [-2.861, 0.973, 1.098, 0.744, 0.232, 0.595], [-3.055, 1.702, 0.901, 0.639, 0.173, 0.718], [3.451, -0.934, 1.096, 0.502, 0.89, 0.387]] B: [[-2.77, -0.712, 0.41, 0.782, 0.713, 0.859], [1.367, 2.116, 0.842, 0.257, 0.504, 0.248], [1.716, 0.519, 0.519, 0.661, 0.573, 0.903], [1.577, -0.324, 0.811, 0.462, 0.54, 0.431], [3.037, -1.452, 0.953, 0.581, 0.687, 0.531], [2.669, -1.872, 0.986, 0.552, 0.48, 0.568], [2.211, -1.887, 0.725, 0.677, 0.554, 1.018], [-2.956, 0.672, 0.826, 0.436, 0.319, 0.465], [-2.626, 1.651, 0.53, 0.537, 0.47, 0.924], [2.995, -0.435, 0.615, 0.566, 0.706, 0.886]] C: [[-2.925, -0.243, 0.295, 0.519, 0.44, 0.711], [1.485, 1.766, 1.018, 0.081, 0.848, 0.483], [1.717, 0.68, 0.214, 0.236, 1.037, 0.434], [1.205, -0.323, 1.125, 0.097, 0.642, 0.242], [3.189, -1.068, 0.599, 0.36, 1.144, 0.939], [2.418, -1.941, 1.167, 0.598, 0.698, 0.702], [1.723, -2.159, 0.821, 0.484, 0.884, 0.696], [-3.03, 0.47, 1.025, 0.789, 0.045, 0.278], [-2.913, 1.461, 0.819, 0.202, 0.085, 1.03], [2.826, -0.221, 0.951, 0.339, 0.752, 1.266]] D: [[-3.135, -0.575, -0.082, 0.411, 0.399, 1.112], [1.76, 1.636, 0.661, -0.118, 0.316, 0.196], [2.067, 0.976, 0.67, 0.22, 0.315, 1.158], [1.439, -0.283, 0.584, 0.087, 0.218, 0.206], [2.848, -1.357, 1.295, 0.653, 0.266, 0.059], [2.99, -1.86, 1.333, 0.578, 0.108, 0.112], [2.118, -1.567, 1.178, 0.323, 0.289, 0.96], [-3.43, 1.005, 1.071, 0.331, 0.71, 0.959], [-3.114, 1.972, 0.571, 0.075, 0.864, 0.441], [2.987, 0.022, 0.923, 0.173, 0.274, 0.482]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_79_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_79_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.456, -1.689, 0.986, 1.238, 0.639, 1.143], [-1.189, -1.791, 0.864, 0.611, 1.379, 1.148]] B: [[1.709, -1.624, 1.232, 0.531, 0.409, 1.263], [-0.537, -2.035, 0.965, 0.162, 1.273, 1.399]] C: [[1.92, -1.614, 0.415, 0.301, 0.956, 1.133], [-0.648, -1.783, 0.191, 0.47, 1.3, 1.09]] D: [[1.863, -1.557, 0.74, 0.792, 0.462, 1.459], [-0.873, -1.717, 0.611, 0.169, 1.157, 1.341]]
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: [[0.348231, 0.123124, -0.929288], [0.936413, -1.6e-05, 0.350899], [0.043189, -0.992391, -0.1153]]; the translation vector: [2.712005, 2.075202, 1.464169], 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: [[1.456, -1.689, 0.986, 1.238, 0.639, 1.143], [-1.189, -1.791, 0.864, 0.611, 1.379, 1.148]] B: [[1.709, -1.624, 1.232, 0.531, 0.409, 1.263], [-0.537, -2.035, 0.965, 0.162, 1.273, 1.399]] C: [[1.92, -1.614, 0.415, 0.301, 0.956, 1.133], [-0.648, -1.783, 0.191, 0.47, 1.3, 1.09]] D: [[1.863, -1.557, 0.74, 0.792, 0.462, 1.459], [-0.873, -1.717, 0.611, 0.169, 1.157, 1.341]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_80_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_80_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.91, 0.435, 1.317, 0.162, -0.028, 0.372], [-1.612, 0.781, 1.119, -0.027, 0.477, 0.779], [-0.879, 0.442, 1.028, 0.015, 0.023, 0.191], [-1.689, 1.721, 1.33, 0.202, 0.203, 0.899]] B: [[-1.22, 0.565, 1.527, 0.13, 0.316, 0.334], [-1.214, 0.573, 1.041, 0.138, 0.311, 0.395], [-1.241, 0.926, 1.496, 0.134, 0.334, 0.376], [-1.254, 1.276, 1.499, 0.14, 0.375, 0.407]] C: [[-0.897, 0.321, 1.25, -0.192, -0.085, 0.628], [-1.027, 0.54, 0.746, 0.155, 0.593, 0.872], [-1.661, 1.141, 1.852, 0.038, 0.687, 0.36], [-1.716, 1.739, 1.744, 0.171, 0.366, 0.735]] D: [[-0.881, 0.818, 1.879, -0.183, 0.463, 0.205], [-0.767, 0.607, 0.616, 0.203, 0.246, 0.191], [-0.822, 0.77, 1.534, -0.248, 0.163, 0.71], [-1.508, 0.961, 1.625, -0.148, 0.39, 0.839]]
Given a RGB image and a depth image, please detect the 3D bounding box of the rack in the scene. The camera pose information includes: the rotation matrix: [[-0.937403, 0.174354, -0.301457], [0.34768, 0.517889, -0.781607], [0.019845, -0.837491, -0.54609]]; the translation vector: [1.513881, 1.499843, 1.388066], 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: [[-0.91, 0.435, 1.317, 0.162, -0.028, 0.372], [-1.612, 0.781, 1.119, -0.027, 0.477, 0.779], [-0.879, 0.442, 1.028, 0.015, 0.023, 0.191], [-1.689, 1.721, 1.33, 0.202, 0.203, 0.899]] B: [[-1.22, 0.565, 1.527, 0.13, 0.316, 0.334], [-1.214, 0.573, 1.041, 0.138, 0.311, 0.395], [-1.241, 0.926, 1.496, 0.134, 0.334, 0.376], [-1.254, 1.276, 1.499, 0.14, 0.375, 0.407]] C: [[-0.897, 0.321, 1.25, -0.192, -0.085, 0.628], [-1.027, 0.54, 0.746, 0.155, 0.593, 0.872], [-1.661, 1.141, 1.852, 0.038, 0.687, 0.36], [-1.716, 1.739, 1.744, 0.171, 0.366, 0.735]] D: [[-0.881, 0.818, 1.879, -0.183, 0.463, 0.205], [-0.767, 0.607, 0.616, 0.203, 0.246, 0.191], [-0.822, 0.77, 1.534, -0.248, 0.163, 0.71], [-1.508, 0.961, 1.625, -0.148, 0.39, 0.839]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_81_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_81_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.79, -0.98, 1.163, 0.352, 0.978, 2.049]] B: [[1.303, -0.943, 0.81, 0.085, 1.431, 2.157]] C: [[0.918, -1.038, 0.78, -0.022, 1.276, 1.887]] D: [[1.132, -1.26, 0.803, 0.268, 1.192, 2.17]]
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: [[-0.15851, 0.420096, -0.893529], [0.981106, -0.034663, -0.190342], [-0.110934, -0.906817, -0.406664]]; the translation vector: [4.004256, 0.910349, 2.578562], 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: [[0.79, -0.98, 1.163, 0.352, 0.978, 2.049]] B: [[1.303, -0.943, 0.81, 0.085, 1.431, 2.157]] C: [[0.918, -1.038, 0.78, -0.022, 1.276, 1.887]] D: [[1.132, -1.26, 0.803, 0.268, 1.192, 2.17]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_82_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_82_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.027, 0.959, 0.116, 0.065, 0.01, 0.668], [-1.502, 1.757, 0.887, 0.168, -0.298, 0.404], [-1.464, 1.693, 1.349, 0.508, -0.033, 0.751], [-1.515, 1.819, 1.174, 0.619, -0.056, 0.931], [-1.32, 1.579, 1.138, 0.221, -0.036, 0.586]] B: [[-1.555, 1.321, -0.005, -0.086, -0.066, 0.68], [-1.503, 1.647, 1.497, 0.094, 0.629, 0.772], [-1.545, 2.057, 0.682, 0.091, -0.365, -0.177], [-1.817, 2.125, 0.639, 0.421, 0.176, 0.148], [-2.148, 2.167, 0.268, 0.654, -0.085, 0.81]] C: [[-1.921, 0.926, 0.476, 0.205, 0.401, 1.004], [-1.317, 1.461, 1.183, 0.482, -0.087, -0.114], [-0.981, 1.858, 0.937, -0.085, -0.01, 0.117], [-1.804, 1.654, 1.126, 0.091, 0.345, 0.125], [-2.134, 1.498, 0.297, 0.016, 0.463, 0.232]] D: [[-2.011, 1.284, 0.385, 0.186, 0.39, 0.566], [-1.266, 1.943, 1.101, 0.313, 0.196, 0.371], [-1.224, 1.994, 0.869, 0.351, 0.116, 0.277], [-1.583, 1.923, 1.035, 0.381, 0.288, 0.498], [-1.707, 1.925, 0.764, 0.426, 0.259, 0.583]]
Given a RGB image and a depth image, please detect the 3D bounding box of the bag in the scene. The camera pose information includes: the rotation matrix: [[0.82141, -0.124481, 0.556588], [-0.562763, -0.33543, 0.755503], [0.092651, -0.933805, -0.345579]]; the translation vector: [1.795382, 2.457259, 1.379582], 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: [[-2.027, 0.959, 0.116, 0.065, 0.01, 0.668], [-1.502, 1.757, 0.887, 0.168, -0.298, 0.404], [-1.464, 1.693, 1.349, 0.508, -0.033, 0.751], [-1.515, 1.819, 1.174, 0.619, -0.056, 0.931], [-1.32, 1.579, 1.138, 0.221, -0.036, 0.586]] B: [[-1.555, 1.321, -0.005, -0.086, -0.066, 0.68], [-1.503, 1.647, 1.497, 0.094, 0.629, 0.772], [-1.545, 2.057, 0.682, 0.091, -0.365, -0.177], [-1.817, 2.125, 0.639, 0.421, 0.176, 0.148], [-2.148, 2.167, 0.268, 0.654, -0.085, 0.81]] C: [[-1.921, 0.926, 0.476, 0.205, 0.401, 1.004], [-1.317, 1.461, 1.183, 0.482, -0.087, -0.114], [-0.981, 1.858, 0.937, -0.085, -0.01, 0.117], [-1.804, 1.654, 1.126, 0.091, 0.345, 0.125], [-2.134, 1.498, 0.297, 0.016, 0.463, 0.232]] D: [[-2.011, 1.284, 0.385, 0.186, 0.39, 0.566], [-1.266, 1.943, 1.101, 0.313, 0.196, 0.371], [-1.224, 1.994, 0.869, 0.351, 0.116, 0.277], [-1.583, 1.923, 1.035, 0.381, 0.288, 0.498], [-1.707, 1.925, 0.764, 0.426, 0.259, 0.583]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_83_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_83_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.036, 1.866, 1.489, 0.307, 0.157, 2.451], [-1.162, -0.721, 0.524, 0.061, 0.505, 0.591], [-1.692, -0.087, 1.909, 0.08, 0.301, 0.1], [-1.275, -0.78, -0.299, 0.662, 0.631, -0.319]] B: [[-1.306, 1.944, 1.27, 0.242, 0.415, 1.919], [-1.846, -0.095, 0.652, 0.668, -0.011, -0.065], [-1.708, -0.182, 1.324, -0.259, 0.382, 0.757], [-0.989, -0.521, 0.267, 0.114, 0.569, -0.144]] C: [[-1.606, 1.5, 1.094, 0.082, 0.444, 2.163], [-1.349, -0.456, 0.266, 0.226, 0.434, 0.139], [-1.295, -0.266, 1.634, 0.118, 0.05, 0.32], [-1.418, -0.408, 0.197, 0.3, 0.329, 0.161]] D: [[-1.696, 1.738, 0.967, 0.285, -0.051, 2.413], [-0.922, -0.569, 0.642, 0.33, 0.259, -0.242], [-0.853, -0.408, 2.052, 0.046, 0.488, 0.615], [-1.165, -0.273, 0.19, 0.107, 0.57, 0.605]]
Given a RGB image and a depth image, please detect the 3D bounding box of the book in the scene. The camera pose information includes: the rotation matrix: [[0.954506, 0.05554, -0.292973], [0.288831, -0.41644, 0.862064], [-0.074127, -0.907465, -0.413536]]; the translation vector: [2.66447, 1.005586, 1.476015], 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: [[-2.036, 1.866, 1.489, 0.307, 0.157, 2.451], [-1.162, -0.721, 0.524, 0.061, 0.505, 0.591], [-1.692, -0.087, 1.909, 0.08, 0.301, 0.1], [-1.275, -0.78, -0.299, 0.662, 0.631, -0.319]] B: [[-1.306, 1.944, 1.27, 0.242, 0.415, 1.919], [-1.846, -0.095, 0.652, 0.668, -0.011, -0.065], [-1.708, -0.182, 1.324, -0.259, 0.382, 0.757], [-0.989, -0.521, 0.267, 0.114, 0.569, -0.144]] C: [[-1.606, 1.5, 1.094, 0.082, 0.444, 2.163], [-1.349, -0.456, 0.266, 0.226, 0.434, 0.139], [-1.295, -0.266, 1.634, 0.118, 0.05, 0.32], [-1.418, -0.408, 0.197, 0.3, 0.329, 0.161]] D: [[-1.696, 1.738, 0.967, 0.285, -0.051, 2.413], [-0.922, -0.569, 0.642, 0.33, 0.259, -0.242], [-0.853, -0.408, 2.052, 0.046, 0.488, 0.615], [-1.165, -0.273, 0.19, 0.107, 0.57, 0.605]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_84_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_84_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.105, -2.287, 1.298, 5.216, 0.87, 2.807], [1.522, -1.359, 1.295, 0.692, 3.211, 2.519], [-1.482, 0.95, 0.954, -0.118, 3.651, 2.351], [2.186, 1.699, 1.104, -0.162, 3.237, 1.812], [-2.278, -2.05, 0.889, 0.84, 1.577, 2.045], [1.673, 0.416, 0.493, 2.003, 0.505, 2.036], [0.961, 0.497, 0.688, -0.227, 0.745, 1.241], [-2.744, -1.281, 0.568, 1.033, 0.219, 1.748], [-1.203, 3.13, 0.749, 0.354, 1.039, 2.281], [0.453, 3.938, 1.358, 3.143, -0.207, 1.101], [1.577, -0.17, 0.647, 1.504, 0.197, 0.91], [0.55, 0.958, 0.74, -0.022, 0.508, 1.915], [-0.28, -2.346, 2.125, 4.551, 0.291, 0.411], [-2.245, 3.374, 2.167, 0.315, 0.57, 1.021], [-1.883, 4.031, 0.791, 0.575, 0.114, 1.338]] B: [[-0.045, -2.933, 0.729, 5.273, 0.38, 1.87], [1.815, -0.872, 1.2, 0.381, 3.199, 2.451], [-1.835, 0.525, 0.883, 0.663, 4.217, 2.299], [1.852, 1.563, 0.117, 0.236, 3.143, 0.945], [-2.89, -2.063, 0.836, 0.206, 1.672, 2.238], [1.326, 0.326, 0.98, 1.535, 0.601, 1.665], [0.245, 0.603, 0.825, -0.004, 1.064, 1.817], [-1.862, -0.49, 1.467, 1.026, 0.012, 1.363], [-1.379, 3.112, 1.213, 0.486, 0.543, 1.682], [0.858, 3.952, 1.318, 3.11, 0.53, 1.733], [1.684, 0.251, 1.226, 1.531, 0.586, 0.576], [0.354, 1.015, 0.82, 0.415, 0.222, 1.857], [-0.273, -2.214, 2.258, 4.248, 0.77, 0.29], [-2.467, 2.65, 1.797, 0.149, 0.618, 1.025], [-2.164, 4.048, 1.03, 0.675, 0.141, 1.166]] C: [[-0.372, -2.705, 1.171, 4.784, 0.513, 2.321], [1.95, -1.245, 1.075, 0.31, 2.969, 2.221], [-1.736, 0.974, 1.065, 0.251, 4.086, 2.141], [2.079, 1.895, 0.614, 0.176, 3.361, 1.364], [-2.712, -1.857, 1.256, 0.344, 1.764, 2.405], [1.315, 0.187, 0.814, 1.511, 0.109, 1.639], [0.561, 0.619, 0.751, 0.075, 0.858, 1.522], [-2.331, -0.947, 0.996, 1.029, 0.105, 1.863], [-0.884, 3.244, 0.946, 0.263, 0.884, 1.941], [0.617, 3.626, 1.612, 2.853, 0.244, 1.318], [1.37, 0.273, 0.995, 1.377, 0.117, 0.425], [0.697, 0.781, 1.082, 0.286, 0.193, 2.222], [-0.516, -2.505, 2.299, 4.488, 0.335, 0.203], [-2.543, 2.889, 1.67, 0.173, 0.883, 0.685], [-1.977, 3.626, 1.246, 0.551, 0.106, 1.503]] D: [[0.035, -2.86, 0.861, 4.728, 0.233, 1.918], [1.546, -1.395, 0.841, 0.548, 3.249, 1.737], [-1.897, 0.52, 1.01, -0.225, 4.45, 2.412], [1.773, 2.047, 0.256, 0.066, 3.328, 1.231], [-3.131, -2.108, 0.842, 0.6, 1.535, 2.741], [1.218, -0.29, 0.461, 1.245, -0.153, 2.098], [0.922, 0.65, 1.084, -0.181, 0.59, 1.506], [-2.276, -0.909, 0.599, 1.207, -0.285, 1.54], [-0.665, 3.431, 1.123, 0.223, 0.621, 1.641], [0.797, 3.806, 2.013, 2.472, 0.677, 1.495], [1.111, 0.293, 1.457, 1.431, 0.551, 0.85], [0.877, 1.185, 1.451, 0.625, -0.09, 2.43], [-0.138, -2.632, 2.484, 4.711, -0.137, 0.648], [-3.024, 2.792, 1.538, -0.201, 1.018, 0.323], [-2.319, 3.937, 1.522, 0.199, 0.289, 1.095]]
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: [[0.99336, -0.011945, -0.114427], [0.103059, -0.349694, 0.931178], [-0.051137, -0.936788, -0.346141]]; the translation vector: [2.948285, 4.432959, 1.460427], 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: [[0.105, -2.287, 1.298, 5.216, 0.87, 2.807], [1.522, -1.359, 1.295, 0.692, 3.211, 2.519], [-1.482, 0.95, 0.954, -0.118, 3.651, 2.351], [2.186, 1.699, 1.104, -0.162, 3.237, 1.812], [-2.278, -2.05, 0.889, 0.84, 1.577, 2.045], [1.673, 0.416, 0.493, 2.003, 0.505, 2.036], [0.961, 0.497, 0.688, -0.227, 0.745, 1.241], [-2.744, -1.281, 0.568, 1.033, 0.219, 1.748], [-1.203, 3.13, 0.749, 0.354, 1.039, 2.281], [0.453, 3.938, 1.358, 3.143, -0.207, 1.101], [1.577, -0.17, 0.647, 1.504, 0.197, 0.91], [0.55, 0.958, 0.74, -0.022, 0.508, 1.915], [-0.28, -2.346, 2.125, 4.551, 0.291, 0.411], [-2.245, 3.374, 2.167, 0.315, 0.57, 1.021], [-1.883, 4.031, 0.791, 0.575, 0.114, 1.338]] B: [[-0.045, -2.933, 0.729, 5.273, 0.38, 1.87], [1.815, -0.872, 1.2, 0.381, 3.199, 2.451], [-1.835, 0.525, 0.883, 0.663, 4.217, 2.299], [1.852, 1.563, 0.117, 0.236, 3.143, 0.945], [-2.89, -2.063, 0.836, 0.206, 1.672, 2.238], [1.326, 0.326, 0.98, 1.535, 0.601, 1.665], [0.245, 0.603, 0.825, -0.004, 1.064, 1.817], [-1.862, -0.49, 1.467, 1.026, 0.012, 1.363], [-1.379, 3.112, 1.213, 0.486, 0.543, 1.682], [0.858, 3.952, 1.318, 3.11, 0.53, 1.733], [1.684, 0.251, 1.226, 1.531, 0.586, 0.576], [0.354, 1.015, 0.82, 0.415, 0.222, 1.857], [-0.273, -2.214, 2.258, 4.248, 0.77, 0.29], [-2.467, 2.65, 1.797, 0.149, 0.618, 1.025], [-2.164, 4.048, 1.03, 0.675, 0.141, 1.166]] C: [[-0.372, -2.705, 1.171, 4.784, 0.513, 2.321], [1.95, -1.245, 1.075, 0.31, 2.969, 2.221], [-1.736, 0.974, 1.065, 0.251, 4.086, 2.141], [2.079, 1.895, 0.614, 0.176, 3.361, 1.364], [-2.712, -1.857, 1.256, 0.344, 1.764, 2.405], [1.315, 0.187, 0.814, 1.511, 0.109, 1.639], [0.561, 0.619, 0.751, 0.075, 0.858, 1.522], [-2.331, -0.947, 0.996, 1.029, 0.105, 1.863], [-0.884, 3.244, 0.946, 0.263, 0.884, 1.941], [0.617, 3.626, 1.612, 2.853, 0.244, 1.318], [1.37, 0.273, 0.995, 1.377, 0.117, 0.425], [0.697, 0.781, 1.082, 0.286, 0.193, 2.222], [-0.516, -2.505, 2.299, 4.488, 0.335, 0.203], [-2.543, 2.889, 1.67, 0.173, 0.883, 0.685], [-1.977, 3.626, 1.246, 0.551, 0.106, 1.503]] D: [[0.035, -2.86, 0.861, 4.728, 0.233, 1.918], [1.546, -1.395, 0.841, 0.548, 3.249, 1.737], [-1.897, 0.52, 1.01, -0.225, 4.45, 2.412], [1.773, 2.047, 0.256, 0.066, 3.328, 1.231], [-3.131, -2.108, 0.842, 0.6, 1.535, 2.741], [1.218, -0.29, 0.461, 1.245, -0.153, 2.098], [0.922, 0.65, 1.084, -0.181, 0.59, 1.506], [-2.276, -0.909, 0.599, 1.207, -0.285, 1.54], [-0.665, 3.431, 1.123, 0.223, 0.621, 1.641], [0.797, 3.806, 2.013, 2.472, 0.677, 1.495], [1.111, 0.293, 1.457, 1.431, 0.551, 0.85], [0.877, 1.185, 1.451, 0.625, -0.09, 2.43], [-0.138, -2.632, 2.484, 4.711, -0.137, 0.648], [-3.024, 2.792, 1.538, -0.201, 1.018, 0.323], [-2.319, 3.937, 1.522, 0.199, 0.289, 1.095]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_85_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_85_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.057, -0.804, 1.454, 0.442, 9.194, 2.993], [-0.24, 3.939, 1.662, 3.88, 0.819, 2.915], [1.686, 1.778, 1.614, 0.375, 4.14, 2.879], [1.518, -0.292, 1.39, 0.502, 0.183, 1.29], [1.407, -0.606, 1.045, 0.392, 0.791, 2.018], [1.569, -2.479, 1.01, 0.478, 3.37, 1.883]] B: [[-1.712, -0.852, 0.991, 0.707, 9.653, 3.103], [0.145, 4.4, 1.88, 4.062, 1.231, 2.667], [1.473, 2.151, 1.876, 0.37, 4.413, 3.184], [1.75, -0.649, 1.384, 0.602, -0.213, 1.435], [1.139, -0.573, 1.304, 0.885, 0.718, 2.242], [1.077, -2.453, 0.735, 0.583, 3.786, 1.438]] C: [[-1.586, -0.802, 1.264, 0.785, 8.752, 2.813], [-0.226, 4.305, 1.323, 3.698, 1.086, 3.015], [1.969, 1.342, 1.623, -0.075, 3.888, 3.299], [1.213, -0.465, 1.751, 0.015, 0.594, 1.001], [0.993, -0.822, 1.254, 0.504, 1.181, 1.943], [1.069, -2.03, 1.336, 0.651, 3.224, 1.602]] D: [[-2.191, -0.396, 1.663, 0.009, 8.751, 3.114], [0.038, 3.888, 1.488, 4.056, 0.477, 3.26], [2.082, 1.991, 1.998, -0.123, 3.891, 2.467], [1.903, -0.079, 0.895, 0.439, 0.291, 0.791], [1.022, -0.776, 0.73, 0.121, 0.449, 1.843], [1.7, -2.034, 1.291, 0.089, 3.481, 2.087]]
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: [[-0.908726, 0.150598, -0.389277], [0.406624, 0.108936, -0.907078], [-0.094198, -0.982575, -0.16023]]; the translation vector: [8.822721, 3.830595, 1.476402], 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: [[-2.057, -0.804, 1.454, 0.442, 9.194, 2.993], [-0.24, 3.939, 1.662, 3.88, 0.819, 2.915], [1.686, 1.778, 1.614, 0.375, 4.14, 2.879], [1.518, -0.292, 1.39, 0.502, 0.183, 1.29], [1.407, -0.606, 1.045, 0.392, 0.791, 2.018], [1.569, -2.479, 1.01, 0.478, 3.37, 1.883]] B: [[-1.712, -0.852, 0.991, 0.707, 9.653, 3.103], [0.145, 4.4, 1.88, 4.062, 1.231, 2.667], [1.473, 2.151, 1.876, 0.37, 4.413, 3.184], [1.75, -0.649, 1.384, 0.602, -0.213, 1.435], [1.139, -0.573, 1.304, 0.885, 0.718, 2.242], [1.077, -2.453, 0.735, 0.583, 3.786, 1.438]] C: [[-1.586, -0.802, 1.264, 0.785, 8.752, 2.813], [-0.226, 4.305, 1.323, 3.698, 1.086, 3.015], [1.969, 1.342, 1.623, -0.075, 3.888, 3.299], [1.213, -0.465, 1.751, 0.015, 0.594, 1.001], [0.993, -0.822, 1.254, 0.504, 1.181, 1.943], [1.069, -2.03, 1.336, 0.651, 3.224, 1.602]] D: [[-2.191, -0.396, 1.663, 0.009, 8.751, 3.114], [0.038, 3.888, 1.488, 4.056, 0.477, 3.26], [2.082, 1.991, 1.998, -0.123, 3.891, 2.467], [1.903, -0.079, 0.895, 0.439, 0.291, 0.791], [1.022, -0.776, 0.73, 0.121, 0.449, 1.843], [1.7, -2.034, 1.291, 0.089, 3.481, 2.087]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_86_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_86_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.406, -0.499, 0.127, 1.547, 0.014, 1.403], [1.954, 0.044, 0.911, 0.502, 4.499, 1.21], [0.82, -1.82, 0.463, 3.057, 0.123, 1.62], [-1.403, -1.396, 1.129, 0.78, 1.058, 1.608], [-1.077, 2.261, 0.337, 0.558, -0.028, 0.985]] B: [[-1.494, -0.876, 0.44, 1.936, 0.339, 1.286], [1.687, 0.61, 0.241, 0.363, 4.812, 0.869], [0.73, -1.681, 0.677, 2.541, -0.283, 1.252], [-1.274, -1.409, 0.377, 0.698, 1.296, 0.85], [-1.137, 2.544, 0.383, 0.033, 0.761, 1.018]] C: [[-2.268, -0.745, 0.912, 1.628, 0.264, 0.904], [1.958, 0.486, 0.503, -0.211, 4.549, 1.566], [-0.072, -2.097, 0.667, 2.893, 0.559, 1.549], [-0.724, -1.085, 0.723, 0.553, 1.77, 1.227], [-0.926, 2.697, 1.076, 0.821, 0.34, 1.204]] D: [[-1.791, -0.394, 0.511, 1.684, 0.11, 0.995], [1.786, 0.422, 0.664, 0.168, 4.577, 1.321], [0.388, -1.877, 0.715, 2.729, 0.147, 1.176], [-1.044, -1.126, 0.648, 0.431, 1.546, 1.277], [-1.081, 2.203, 0.66, 0.386, 0.403, 0.882]]
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: [[-0.997112, 0.02462, 0.071841], [-0.04661, 0.548461, -0.834876], [-0.059957, -0.835814, -0.545729]]; the translation vector: [4.834615, 3.436689, 1.398379], 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: [[-1.406, -0.499, 0.127, 1.547, 0.014, 1.403], [1.954, 0.044, 0.911, 0.502, 4.499, 1.21], [0.82, -1.82, 0.463, 3.057, 0.123, 1.62], [-1.403, -1.396, 1.129, 0.78, 1.058, 1.608], [-1.077, 2.261, 0.337, 0.558, -0.028, 0.985]] B: [[-1.494, -0.876, 0.44, 1.936, 0.339, 1.286], [1.687, 0.61, 0.241, 0.363, 4.812, 0.869], [0.73, -1.681, 0.677, 2.541, -0.283, 1.252], [-1.274, -1.409, 0.377, 0.698, 1.296, 0.85], [-1.137, 2.544, 0.383, 0.033, 0.761, 1.018]] C: [[-2.268, -0.745, 0.912, 1.628, 0.264, 0.904], [1.958, 0.486, 0.503, -0.211, 4.549, 1.566], [-0.072, -2.097, 0.667, 2.893, 0.559, 1.549], [-0.724, -1.085, 0.723, 0.553, 1.77, 1.227], [-0.926, 2.697, 1.076, 0.821, 0.34, 1.204]] D: [[-1.791, -0.394, 0.511, 1.684, 0.11, 0.995], [1.786, 0.422, 0.664, 0.168, 4.577, 1.321], [0.388, -1.877, 0.715, 2.729, 0.147, 1.176], [-1.044, -1.126, 0.648, 0.431, 1.546, 1.277], [-1.081, 2.203, 0.66, 0.386, 0.403, 0.882]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_87_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_87_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.113, 0.087, 0.564, 0.343, 0.527, 0.305], [0.507, 0.467, 0.458, 0.596, 0.504, 0.317], [0.58, 0.988, 0.644, 0.601, 0.651, 0.477], [0.182, 1.04, 0.677, 0.777, 0.505, 0.512], [1.732, 0.733, 0.527, 0.634, 0.573, 0.263], [1.609, 1.049, 0.659, 0.686, 0.387, 0.426]] B: [[0.129, 0.521, 0.187, 0.313, 0.856, 0.592], [0.981, 0.918, 0.313, 0.429, 0.812, 0.551], [0.233, 0.816, 0.228, 0.26, 0.574, 0.165], [-0.257, 0.76, 1.031, 0.337, 0.304, 1.005], [1.703, 1.1, 0.991, 1.058, 0.84, 0.596], [1.167, 0.943, 0.538, 0.487, 0.187, 0.143]] C: [[0.577, 0.356, 0.8, 0.107, 0.25, -0.032], [0.156, 0.937, 0.399, 0.676, 0.726, 0.633], [0.215, 0.658, 0.629, 0.763, 0.937, 0.472], [0.377, 0.594, 0.698, 1.038, 0.047, 0.378], [1.421, 1.109, 0.213, 0.954, 0.857, -0.124], [1.144, 1.512, 0.746, 0.326, 0.254, -0.001]] D: [[-0.375, 0.568, 0.757, 0.525, 0.71, 0.684], [0.596, 0.141, 0.679, 0.896, 0.714, 0.623], [0.506, 1.007, 0.844, 0.63, 0.899, 0.696], [-0.281, 1.187, 1.15, 1.186, 0.539, 1.005], [1.823, 0.702, 0.5, 0.724, 0.202, 0.553], [1.882, 1.516, 0.881, 1.085, 0.712, 0.444]]
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: [[-0.971613, -0.06682, 0.226943], [-0.235147, 0.378036, -0.89543], [-0.02596, -0.923376, -0.383017]]; the translation vector: [2.775299, 4.618156, 1.427592], 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: [[0.113, 0.087, 0.564, 0.343, 0.527, 0.305], [0.507, 0.467, 0.458, 0.596, 0.504, 0.317], [0.58, 0.988, 0.644, 0.601, 0.651, 0.477], [0.182, 1.04, 0.677, 0.777, 0.505, 0.512], [1.732, 0.733, 0.527, 0.634, 0.573, 0.263], [1.609, 1.049, 0.659, 0.686, 0.387, 0.426]] B: [[0.129, 0.521, 0.187, 0.313, 0.856, 0.592], [0.981, 0.918, 0.313, 0.429, 0.812, 0.551], [0.233, 0.816, 0.228, 0.26, 0.574, 0.165], [-0.257, 0.76, 1.031, 0.337, 0.304, 1.005], [1.703, 1.1, 0.991, 1.058, 0.84, 0.596], [1.167, 0.943, 0.538, 0.487, 0.187, 0.143]] C: [[0.577, 0.356, 0.8, 0.107, 0.25, -0.032], [0.156, 0.937, 0.399, 0.676, 0.726, 0.633], [0.215, 0.658, 0.629, 0.763, 0.937, 0.472], [0.377, 0.594, 0.698, 1.038, 0.047, 0.378], [1.421, 1.109, 0.213, 0.954, 0.857, -0.124], [1.144, 1.512, 0.746, 0.326, 0.254, -0.001]] D: [[-0.375, 0.568, 0.757, 0.525, 0.71, 0.684], [0.596, 0.141, 0.679, 0.896, 0.714, 0.623], [0.506, 1.007, 0.844, 0.63, 0.899, 0.696], [-0.281, 1.187, 1.15, 1.186, 0.539, 1.005], [1.823, 0.702, 0.5, 0.724, 0.202, 0.553], [1.882, 1.516, 0.881, 1.085, 0.712, 0.444]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_88_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_88_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.081, -2.379, 1.113, 0.296, 0.447, 1.93], [-2.179, -2.328, 1.113, 1.155, -0.055, 2.191], [0.187, -2.593, 1.0, 1.525, -0.011, 1.61]] B: [[0.156, -1.688, 0.672, 1.099, 0.512, 1.787], [-1.601, -2.386, 1.059, 0.494, 0.257, 2.331], [1.089, -2.9, 1.408, 0.896, 0.19, 1.392]] C: [[-0.153, -1.917, 0.934, 0.637, 0.572, 1.999], [-2.071, -2.511, 0.942, 0.893, 0.199, 2.089], [0.673, -2.564, 1.392, 1.046, 0.131, 1.552]] D: [[0.141, -1.904, 0.579, 0.681, 0.731, 2.01], [-1.907, -2.369, 0.924, 0.512, 0.574, 2.053], [0.733, -2.632, 1.326, 0.995, 0.386, 1.64]]
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: [[-0.086843, 0.425015, -0.901011], [0.995696, 0.066429, -0.064634], [0.032383, -0.902745, -0.428955]]; the translation vector: [4.261571, 5.85756, 1.66629], 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: [[0.081, -2.379, 1.113, 0.296, 0.447, 1.93], [-2.179, -2.328, 1.113, 1.155, -0.055, 2.191], [0.187, -2.593, 1.0, 1.525, -0.011, 1.61]] B: [[0.156, -1.688, 0.672, 1.099, 0.512, 1.787], [-1.601, -2.386, 1.059, 0.494, 0.257, 2.331], [1.089, -2.9, 1.408, 0.896, 0.19, 1.392]] C: [[-0.153, -1.917, 0.934, 0.637, 0.572, 1.999], [-2.071, -2.511, 0.942, 0.893, 0.199, 2.089], [0.673, -2.564, 1.392, 1.046, 0.131, 1.552]] D: [[0.141, -1.904, 0.579, 0.681, 0.731, 2.01], [-1.907, -2.369, 0.924, 0.512, 0.574, 2.053], [0.733, -2.632, 1.326, 0.995, 0.386, 1.64]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_89_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_89_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.066, -4.092, 0.322, 1.809, 0.144, 0.711], [-0.452, -3.998, 0.399, -0.022, -0.207, 0.313]] B: [[0.967, -4.137, 0.415, 1.862, 0.896, 0.809], [-0.541, -3.922, 0.752, 0.892, 0.695, 1.151]] C: [[0.859, -4.189, 1.178, 1.424, -0.037, 1.276], [-0.399, -4.209, 0.397, 0.399, 0.232, 1.02]] D: [[0.733, -4.146, 0.771, 1.808, 0.42, 0.818], [-0.752, -4.266, 0.836, 0.396, 0.285, 0.778]]
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: [[0.504428, 0.479717, -0.717931], [0.860003, -0.204862, 0.467362], [0.077124, -0.853173, -0.515896]]; the translation vector: [4.973708, 0.412451, 1.573636], 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: [[1.066, -4.092, 0.322, 1.809, 0.144, 0.711], [-0.452, -3.998, 0.399, -0.022, -0.207, 0.313]] B: [[0.967, -4.137, 0.415, 1.862, 0.896, 0.809], [-0.541, -3.922, 0.752, 0.892, 0.695, 1.151]] C: [[0.859, -4.189, 1.178, 1.424, -0.037, 1.276], [-0.399, -4.209, 0.397, 0.399, 0.232, 1.02]] D: [[0.733, -4.146, 0.771, 1.808, 0.42, 0.818], [-0.752, -4.266, 0.836, 0.396, 0.285, 0.778]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_90_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_90_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-2.356, -1.033, 0.487, 1.053, 0.829, 1.337]] B: [[-1.861, -0.729, 0.172, 1.066, 1.25, 1.068]] C: [[-2.075, -0.604, 0.467, 1.418, 0.63, 1.288]] D: [[-2.244, -1.03, 0.539, 1.266, 0.775, 0.934]]
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: [[-0.132001, -0.567775, 0.812532], [-0.991224, 0.069667, -0.112349], [0.007182, -0.820231, -0.571988]]; the translation vector: [2.407685, 4.450429, 1.359714], 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: [[-2.356, -1.033, 0.487, 1.053, 0.829, 1.337]] B: [[-1.861, -0.729, 0.172, 1.066, 1.25, 1.068]] C: [[-2.075, -0.604, 0.467, 1.418, 0.63, 1.288]] D: [[-2.244, -1.03, 0.539, 1.266, 0.775, 0.934]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_91_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_91_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.569, 0.211, 0.319, 0.687, 0.401, 0.55], [-0.378, 2.451, 0.757, 1.108, 0.785, 1.152], [-0.442, -3.047, 0.599, 0.595, 0.53, 0.698], [-0.671, -2.103, 0.492, 0.589, 0.785, 1.436], [-0.536, -2.312, 0.381, 0.676, 0.927, 0.8], [0.694, -2.162, -0.024, 0.318, 0.238, 1.069], [0.8, -2.531, 0.157, 0.887, 0.472, 0.605], [-0.017, 0.764, 0.766, 0.464, 0.143, 1.084]] B: [[-0.14, -0.504, 0.958, 0.996, 0.333, 0.616], [-0.523, 2.406, 0.116, 1.014, 1.032, 0.584], [-1.041, -3.534, 0.221, 1.124, 0.509, 0.64], [-1.178, -1.955, 0.316, 0.454, 0.967, 0.762], [-0.074, -2.655, 0.057, 0.407, 0.341, 0.817], [0.498, -1.8, 0.525, 0.171, 1.003, 0.793], [0.349, -2.636, 0.785, 0.651, 0.822, 0.565], [-0.067, 1.46, 0.267, 0.865, 0.829, 0.524]] C: [[0.244, -0.138, 0.489, 0.688, 0.662, 1.02], [-0.663, 2.462, 0.398, 0.618, 0.647, 0.654], [-0.762, -3.211, 0.433, 0.631, 0.73, 0.899], [-0.866, -2.412, 0.459, 0.652, 0.663, 0.995], [-0.182, -2.73, 0.386, 0.664, 0.667, 0.841], [0.386, -2.023, 0.44, 0.586, 0.689, 0.943], [0.543, -2.581, 0.583, 0.445, 0.548, 0.641], [0.339, 1.261, 0.575, 0.571, 0.572, 0.783]] D: [[0.09, 0.046, 0.862, 0.335, 0.771, 1.401], [-0.263, 2.607, 0.862, 0.364, 1.092, 0.886], [-1.02, -3.334, 0.931, 1.001, 0.759, 0.875], [-0.888, -2.153, 0.017, 0.223, 0.261, 0.633], [-0.543, -2.555, 0.32, 1.086, 0.816, 0.575], [0.862, -2.2, 0.258, 0.465, 0.987, 0.866], [0.065, -2.865, 0.495, 0.697, 0.945, 0.331], [0.317, 1.592, 1.019, 0.326, 0.876, 0.791]]
Given a RGB image and a depth image, please detect the 3D bounding box of the office chair in the scene. The camera pose information includes: the rotation matrix: [[0.672393, -0.274439, 0.687438], [-0.739855, -0.221079, 0.635404], [-0.022402, -0.935846, -0.351697]]; the translation vector: [3.802358, 2.110255, 1.494557], 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: [[0.569, 0.211, 0.319, 0.687, 0.401, 0.55], [-0.378, 2.451, 0.757, 1.108, 0.785, 1.152], [-0.442, -3.047, 0.599, 0.595, 0.53, 0.698], [-0.671, -2.103, 0.492, 0.589, 0.785, 1.436], [-0.536, -2.312, 0.381, 0.676, 0.927, 0.8], [0.694, -2.162, -0.024, 0.318, 0.238, 1.069], [0.8, -2.531, 0.157, 0.887, 0.472, 0.605], [-0.017, 0.764, 0.766, 0.464, 0.143, 1.084]] B: [[-0.14, -0.504, 0.958, 0.996, 0.333, 0.616], [-0.523, 2.406, 0.116, 1.014, 1.032, 0.584], [-1.041, -3.534, 0.221, 1.124, 0.509, 0.64], [-1.178, -1.955, 0.316, 0.454, 0.967, 0.762], [-0.074, -2.655, 0.057, 0.407, 0.341, 0.817], [0.498, -1.8, 0.525, 0.171, 1.003, 0.793], [0.349, -2.636, 0.785, 0.651, 0.822, 0.565], [-0.067, 1.46, 0.267, 0.865, 0.829, 0.524]] C: [[0.244, -0.138, 0.489, 0.688, 0.662, 1.02], [-0.663, 2.462, 0.398, 0.618, 0.647, 0.654], [-0.762, -3.211, 0.433, 0.631, 0.73, 0.899], [-0.866, -2.412, 0.459, 0.652, 0.663, 0.995], [-0.182, -2.73, 0.386, 0.664, 0.667, 0.841], [0.386, -2.023, 0.44, 0.586, 0.689, 0.943], [0.543, -2.581, 0.583, 0.445, 0.548, 0.641], [0.339, 1.261, 0.575, 0.571, 0.572, 0.783]] D: [[0.09, 0.046, 0.862, 0.335, 0.771, 1.401], [-0.263, 2.607, 0.862, 0.364, 1.092, 0.886], [-1.02, -3.334, 0.931, 1.001, 0.759, 0.875], [-0.888, -2.153, 0.017, 0.223, 0.261, 0.633], [-0.543, -2.555, 0.32, 1.086, 0.816, 0.575], [0.862, -2.2, 0.258, 0.465, 0.987, 0.866], [0.065, -2.865, 0.495, 0.697, 0.945, 0.331], [0.317, 1.592, 1.019, 0.326, 0.876, 0.791]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_92_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_92_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.126, -1.376, 0.347, 0.441, 1.044, 0.747]] B: [[-0.707, -1.056, 0.436, 0.481, 0.775, 0.862]] C: [[-1.072, -0.581, 0.729, 0.634, 0.411, 0.815]] D: [[-1.2, -0.714, 0.073, 0.598, 1.239, 1.356]]
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: [[-0.943065, -0.17817, 0.280864], [-0.332105, 0.550897, -0.765649], [-0.018311, -0.815333, -0.578703]]; the translation vector: [2.74599, 1.673222, 1.294065], 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, -1.376, 0.347, 0.441, 1.044, 0.747]] B: [[-0.707, -1.056, 0.436, 0.481, 0.775, 0.862]] C: [[-1.072, -0.581, 0.729, 0.634, 0.411, 0.815]] D: [[-1.2, -0.714, 0.073, 0.598, 1.239, 1.356]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_93_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_93_1.png" ]
B
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-1.746, -0.676, 1.548, 0.354, 0.507, 0.554], [1.278, -0.21, 2.039, 0.253, 0.159, 0.277], [1.354, -0.174, 2.085, 0.187, 0.25, 0.284], [1.365, 0.302, 2.07, 0.178, 0.146, 0.195], [1.395, 1.775, 0.709, 0.116, 0.082, 0.239], [0.108, -1.232, 0.61, 0.37, 0.243, 0.232]] B: [[-2.116, -0.405, 1.974, 0.197, 0.992, 0.793], [1.595, -0.115, 1.898, 0.53, -0.095, 0.207], [1.74, -0.462, 1.811, 0.459, 0.366, 0.195], [1.756, -0.03, 2.139, 0.506, -0.218, -0.14], [1.496, 1.894, 0.22, -0.344, -0.274, 0.329], [0.12, -1.361, 0.247, 0.677, 0.431, 0.41]] C: [[-2.099, -0.677, 1.826, 0.111, 0.048, 0.88], [1.179, -0.084, 2.064, 0.353, -0.335, 0.047], [1.283, -0.017, 2.251, 0.548, 0.539, -0.139], [1.054, -0.131, 1.995, -0.052, 0.135, -0.266], [1.813, 1.809, 0.298, 0.268, -0.092, 0.575], [0.507, -1.135, 0.122, 0.102, 0.682, -0.107]] D: [[-2.013, -0.781, 2.031, 0.552, 0.053, 0.962], [1.49, 0.048, 1.694, 0.076, -0.303, 0.184], [1.646, 0.043, 2.403, 0.082, 0.014, 0.773], [1.068, 0.187, 2.309, 0.672, -0.201, 0.291], [1.861, 1.412, 0.913, 0.343, -0.022, 0.312], [-0.111, -1.095, 0.386, 0.723, 0.064, 0.108]]
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: [[0.493838, -0.420518, 0.76111], [-0.864926, -0.147366, 0.479777], [-0.089593, -0.895236, -0.436493]]; the translation vector: [0.736944, 2.108944, 1.402726], 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: [[-1.746, -0.676, 1.548, 0.354, 0.507, 0.554], [1.278, -0.21, 2.039, 0.253, 0.159, 0.277], [1.354, -0.174, 2.085, 0.187, 0.25, 0.284], [1.365, 0.302, 2.07, 0.178, 0.146, 0.195], [1.395, 1.775, 0.709, 0.116, 0.082, 0.239], [0.108, -1.232, 0.61, 0.37, 0.243, 0.232]] B: [[-2.116, -0.405, 1.974, 0.197, 0.992, 0.793], [1.595, -0.115, 1.898, 0.53, -0.095, 0.207], [1.74, -0.462, 1.811, 0.459, 0.366, 0.195], [1.756, -0.03, 2.139, 0.506, -0.218, -0.14], [1.496, 1.894, 0.22, -0.344, -0.274, 0.329], [0.12, -1.361, 0.247, 0.677, 0.431, 0.41]] C: [[-2.099, -0.677, 1.826, 0.111, 0.048, 0.88], [1.179, -0.084, 2.064, 0.353, -0.335, 0.047], [1.283, -0.017, 2.251, 0.548, 0.539, -0.139], [1.054, -0.131, 1.995, -0.052, 0.135, -0.266], [1.813, 1.809, 0.298, 0.268, -0.092, 0.575], [0.507, -1.135, 0.122, 0.102, 0.682, -0.107]] D: [[-2.013, -0.781, 2.031, 0.552, 0.053, 0.962], [1.49, 0.048, 1.694, 0.076, -0.303, 0.184], [1.646, 0.043, 2.403, 0.082, 0.014, 0.773], [1.068, 0.187, 2.309, 0.672, -0.201, 0.291], [1.861, 1.412, 0.913, 0.343, -0.022, 0.312], [-0.111, -1.095, 0.386, 0.723, 0.064, 0.108]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_94_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_94_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.095, 0.369, 0.896, 1.864, 0.389, -0.037]] B: [[0.821, 1.024, 0.461, 1.589, 1.059, 0.417]] C: [[0.235, 0.419, 0.494, 1.232, 0.977, 0.5]] D: [[0.531, 0.805, 0.846, 1.569, 0.745, 0.229]]
Given a RGB image and a depth image, please detect the 3D bounding box of the counter in the scene. The camera pose information includes: the rotation matrix: [[0.882784, 0.25224, -0.396318], [0.469583, -0.498211, 0.728888], [-0.013595, -0.829554, -0.55826]]; the translation vector: [3.463734, 1.394934, 1.262723], 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: [[0.095, 0.369, 0.896, 1.864, 0.389, -0.037]] B: [[0.821, 1.024, 0.461, 1.589, 1.059, 0.417]] C: [[0.235, 0.419, 0.494, 1.232, 0.977, 0.5]] D: [[0.531, 0.805, 0.846, 1.569, 0.745, 0.229]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_95_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_95_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.71, -0.427, 1.41, -0.084, 0.707, -0.208]] B: [[-1.108, -0.854, 1.201, 0.423, 0.471, 0.68]] C: [[-1.305, -0.718, 1.12, 0.437, 0.021, 0.653]] D: [[-1.106, -0.393, 0.937, 0.241, 0.317, 0.242]]
Given a RGB image and a depth image, please detect the 3D bounding box of the tray in the scene. The camera pose information includes: the rotation matrix: [[-0.998162, -0.007354, -0.06016], [0.055338, 0.294228, -0.954132], [0.024717, -0.955707, -0.293281]]; the translation vector: [1.687981, 4.43329, 1.569003], 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: [[-0.71, -0.427, 1.41, -0.084, 0.707, -0.208]] B: [[-1.108, -0.854, 1.201, 0.423, 0.471, 0.68]] C: [[-1.305, -0.718, 1.12, 0.437, 0.021, 0.653]] D: [[-1.106, -0.393, 0.937, 0.241, 0.317, 0.242]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_96_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_96_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.882, 1.56, 0.388, 0.537, 1.676, 0.722], [-0.93, 1.385, 0.286, 0.589, 0.589, 0.521], [-0.937, -1.858, 0.442, 0.583, 0.58, 0.542]] B: [[1.943, 1.267, 0.682, 0.711, 1.577, 0.374], [-1.208, 1.812, -0.196, 1.059, 0.169, 0.521], [-1.321, -1.601, 0.071, 0.85, 0.083, 0.59]] C: [[2.195, 1.182, 0.758, 0.43, 1.952, 0.35], [-1.23, 1.71, 0.54, 0.173, 0.389, 0.39], [-0.765, -1.788, 0.133, 0.882, 0.65, 0.803]] D: [[1.615, 1.264, -0.077, 0.87, 1.187, 0.662], [-0.905, 1.561, 0.641, 0.894, 0.612, 0.112], [-0.628, -2.319, 0.352, 0.102, 0.924, 0.919]]
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: [[-0.530794, 0.426739, -0.732224], [0.841151, 0.159702, -0.516681], [-0.10355, -0.890162, -0.443721]]; the translation vector: [5.418979, 4.373359, 1.385162], 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: [[1.882, 1.56, 0.388, 0.537, 1.676, 0.722], [-0.93, 1.385, 0.286, 0.589, 0.589, 0.521], [-0.937, -1.858, 0.442, 0.583, 0.58, 0.542]] B: [[1.943, 1.267, 0.682, 0.711, 1.577, 0.374], [-1.208, 1.812, -0.196, 1.059, 0.169, 0.521], [-1.321, -1.601, 0.071, 0.85, 0.083, 0.59]] C: [[2.195, 1.182, 0.758, 0.43, 1.952, 0.35], [-1.23, 1.71, 0.54, 0.173, 0.389, 0.39], [-0.765, -1.788, 0.133, 0.882, 0.65, 0.803]] D: [[1.615, 1.264, -0.077, 0.87, 1.187, 0.662], [-0.905, 1.561, 0.641, 0.894, 0.612, 0.112], [-0.628, -2.319, 0.352, 0.102, 0.924, 0.919]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_97_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_97_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[0.419, -1.385, 0.468, 0.603, 0.548, -0.002]] B: [[0.568, -0.742, 0.118, 0.677, 0.387, 0.514]] C: [[0.186, -1.693, 0.012, 1.09, 0.395, 0.456]] D: [[0.461, -1.208, 0.23, 0.711, 0.358, 0.459]]
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: [[0.695296, -0.421579, 0.582095], [-0.717067, -0.351947, 0.601622], [-0.048765, -0.835707, -0.547007]]; the translation vector: [2.470866, 0.652559, 1.473924], 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: [[0.419, -1.385, 0.468, 0.603, 0.548, -0.002]] B: [[0.568, -0.742, 0.118, 0.677, 0.387, 0.514]] C: [[0.186, -1.693, 0.012, 1.09, 0.395, 0.456]] D: [[0.461, -1.208, 0.23, 0.711, 0.358, 0.459]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_98_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_98_1.png" ]
D
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[-0.786, 0.016, 0.222, 1.217, 0.653, 0.431]] B: [[-1.037, -0.227, 0.31, 1.564, 0.876, 0.857]] C: [[-1.111, -0.46, 0.292, 1.65, 0.975, 0.105]] D: [[-0.725, -0.136, -0.167, 0.877, 0.479, 0.631]]
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: [[0.408988, -0.323891, 0.853126], [-0.912443, -0.158736, 0.37716], [0.013263, -0.932683, -0.360453]]; the translation vector: [3.672612, 2.990265, 1.494339], 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: [[-0.786, 0.016, 0.222, 1.217, 0.653, 0.431]] B: [[-1.037, -0.227, 0.31, 1.564, 0.876, 0.857]] C: [[-1.111, -0.46, 0.292, 1.65, 0.975, 0.105]] D: [[-0.725, -0.136, -0.167, 0.877, 0.479, 0.631]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_99_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_99_1.png" ]
A
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.78, -0.369, 0.924, 0.56, 5.207, 1.466], [-1.469, 1.84, 1.529, 0.1, 3.46, 1.026], [1.603, 3.517, 0.975, 0.924, 0.045, 0.875], [-1.453, 3.239, 1.664, 0.75, -0.019, 1.939], [-1.132, -0.282, 1.01, 0.6, 1.619, 1.743], [-0.943, -1.737, 1.065, 0.938, -0.129, 1.932], [-0.462, -1.272, 0.976, 0.13, 0.263, 2.111], [-0.647, -3.37, 0.86, -0.005, 1.127, 1.632], [0.759, -3.788, 0.905, 0.472, 0.723, 1.787], [1.365, -2.765, 1.105, 0.336, 0.467, 1.277]] B: [[1.074, -0.516, 1.118, -0.086, 5.725, 2.158], [-1.396, 2.343, 1.47, -0.008, 3.692, 1.57], [1.315, 3.398, 1.101, 1.035, 0.612, 0.867], [-0.97, 3.198, 1.01, 0.853, 0.483, 1.503], [-1.961, -0.579, 0.799, 0.47, 0.959, 1.354], [-0.792, -1.093, 0.831, 0.98, 0.15, 1.422], [-0.764, -1.052, 0.538, 0.169, -0.099, 1.83], [-0.948, -3.534, 0.813, 0.512, 1.974, 2.262], [1.309, -3.86, 1.13, 0.074, 1.177, 0.95], [0.842, -2.685, 1.111, 0.225, 0.622, 1.342]] C: [[1.398, -0.078, 0.847, 0.238, 5.699, 1.741], [-1.453, 1.912, 1.74, 0.206, 3.243, 1.354], [1.514, 3.636, 0.972, 1.079, 0.266, 0.762], [-1.064, 3.584, 1.382, 0.689, 0.248, 1.654], [-1.552, -0.739, 0.879, 0.227, 1.257, 1.692], [-1.211, -1.342, 0.86, 0.655, 0.096, 1.73], [-0.902, -1.484, 0.9, 0.087, 0.331, 1.816], [-0.874, -3.114, 1.006, 0.184, 1.508, 2.084], [0.921, -3.404, 0.668, 0.136, 1.137, 1.434], [1.157, -2.863, 0.703, 0.531, 0.128, 1.521]] D: [[1.025, -0.536, 0.699, 0.592, 5.958, 2.064], [-1.605, 1.792, 2.153, -0.235, 3.185, 1.084], [1.02, 3.68, 1.082, 1.526, 0.082, 0.582], [-1.08, 3.95, 0.986, 0.299, -0.139, 1.856], [-1.893, -0.998, 0.689, 0.259, 1.727, 1.918], [-1.034, -1.551, 0.605, 0.948, 0.46, 1.541], [-1.095, -1.908, 1.355, 0.164, 0.298, 1.555], [-0.914, -3.165, 0.928, -0.077, 1.779, 1.639], [0.568, -3.209, 0.575, 0.598, 1.246, 1.226], [1.226, -3.252, 0.43, 0.831, 0.263, 1.38]]
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: [[-0.52463, -0.231347, 0.819293], [-0.850589, 0.102279, -0.515789], [0.03553, -0.96748, -0.25044]]; the translation vector: [5.897326, 2.792535, 1.553822], 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: [[1.78, -0.369, 0.924, 0.56, 5.207, 1.466], [-1.469, 1.84, 1.529, 0.1, 3.46, 1.026], [1.603, 3.517, 0.975, 0.924, 0.045, 0.875], [-1.453, 3.239, 1.664, 0.75, -0.019, 1.939], [-1.132, -0.282, 1.01, 0.6, 1.619, 1.743], [-0.943, -1.737, 1.065, 0.938, -0.129, 1.932], [-0.462, -1.272, 0.976, 0.13, 0.263, 2.111], [-0.647, -3.37, 0.86, -0.005, 1.127, 1.632], [0.759, -3.788, 0.905, 0.472, 0.723, 1.787], [1.365, -2.765, 1.105, 0.336, 0.467, 1.277]] B: [[1.074, -0.516, 1.118, -0.086, 5.725, 2.158], [-1.396, 2.343, 1.47, -0.008, 3.692, 1.57], [1.315, 3.398, 1.101, 1.035, 0.612, 0.867], [-0.97, 3.198, 1.01, 0.853, 0.483, 1.503], [-1.961, -0.579, 0.799, 0.47, 0.959, 1.354], [-0.792, -1.093, 0.831, 0.98, 0.15, 1.422], [-0.764, -1.052, 0.538, 0.169, -0.099, 1.83], [-0.948, -3.534, 0.813, 0.512, 1.974, 2.262], [1.309, -3.86, 1.13, 0.074, 1.177, 0.95], [0.842, -2.685, 1.111, 0.225, 0.622, 1.342]] C: [[1.398, -0.078, 0.847, 0.238, 5.699, 1.741], [-1.453, 1.912, 1.74, 0.206, 3.243, 1.354], [1.514, 3.636, 0.972, 1.079, 0.266, 0.762], [-1.064, 3.584, 1.382, 0.689, 0.248, 1.654], [-1.552, -0.739, 0.879, 0.227, 1.257, 1.692], [-1.211, -1.342, 0.86, 0.655, 0.096, 1.73], [-0.902, -1.484, 0.9, 0.087, 0.331, 1.816], [-0.874, -3.114, 1.006, 0.184, 1.508, 2.084], [0.921, -3.404, 0.668, 0.136, 1.137, 1.434], [1.157, -2.863, 0.703, 0.531, 0.128, 1.521]] D: [[1.025, -0.536, 0.699, 0.592, 5.958, 2.064], [-1.605, 1.792, 2.153, -0.235, 3.185, 1.084], [1.02, 3.68, 1.082, 1.526, 0.082, 0.582], [-1.08, 3.95, 0.986, 0.299, -0.139, 1.856], [-1.893, -0.998, 0.689, 0.259, 1.727, 1.918], [-1.034, -1.551, 0.605, 0.948, 0.46, 1.541], [-1.095, -1.908, 1.355, 0.164, 0.298, 1.555], [-0.914, -3.165, 0.928, -0.077, 1.779, 1.639], [0.568, -3.209, 0.575, 0.598, 1.246, 1.226], [1.226, -3.252, 0.43, 0.831, 0.263, 1.38]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_100_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_100_1.png" ]
C
threeD_Object_Detection
3d image
SCANNET_threed_bbox_detection
A: [[1.346, -1.632, 0.468, 0.228, 0.435, 0.463], [1.166, -1.379, 0.353, 0.04, 0.901, -0.25], [1.058, -1.308, -0.427, 0.416, 0.148, -0.261], [1.588, -1.671, -0.302, 0.296, 0.611, 0.478], [1.29, -1.513, 0.294, 0.468, 0.683, 0.487]] B: [[1.331, -1.83, 0.338, 0.317, 0.297, 0.192], [1.086, -1.365, 0.034, 0.38, 0.508, 0.129], [1.22, -1.567, 0.058, 0.382, 0.375, 0.145], [1.153, -2.04, 0.055, 0.29, 0.371, 0.11], [1.391, -1.481, 0.041, 0.386, 0.621, 0.13]] C: [[1.118, -1.374, 0.329, -0.089, 0.113, 0.27], [1.322, -1.418, -0.243, 0.677, 0.961, -0.031], [1.042, -1.495, -0.402, 0.189, 0.317, 0.229], [1.027, -2.005, 0.379, 0.337, 0.077, -0.062], [1.617, -1.294, 0.41, -0.08, 0.836, 0.171]] D: [[1.601, -1.491, 0.468, 0.181, 0.51, -0.093], [0.965, -1.654, 0.463, 0.875, 0.478, 0.252], [1.604, -1.87, -0.185, 0.098, 0.676, 0.612], [1.637, -2.272, -0.12, 0.307, 0.185, 0.124], [1.563, -1.727, 0.204, 0.781, 0.373, 0.021]]
Given a RGB image and a depth image, please detect the 3D bounding box of the shoes in the scene. The camera pose information includes: the rotation matrix: [[-0.079656, -0.319192, 0.944337], [-0.994012, 0.096527, -0.051219], [-0.074805, -0.942762, -0.324969]]; the translation vector: [4.3352, 2.935251, 1.464921], 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: [[1.346, -1.632, 0.468, 0.228, 0.435, 0.463], [1.166, -1.379, 0.353, 0.04, 0.901, -0.25], [1.058, -1.308, -0.427, 0.416, 0.148, -0.261], [1.588, -1.671, -0.302, 0.296, 0.611, 0.478], [1.29, -1.513, 0.294, 0.468, 0.683, 0.487]] B: [[1.331, -1.83, 0.338, 0.317, 0.297, 0.192], [1.086, -1.365, 0.034, 0.38, 0.508, 0.129], [1.22, -1.567, 0.058, 0.382, 0.375, 0.145], [1.153, -2.04, 0.055, 0.29, 0.371, 0.11], [1.391, -1.481, 0.041, 0.386, 0.621, 0.13]] C: [[1.118, -1.374, 0.329, -0.089, 0.113, 0.27], [1.322, -1.418, -0.243, 0.677, 0.961, -0.031], [1.042, -1.495, -0.402, 0.189, 0.317, 0.229], [1.027, -2.005, 0.379, 0.337, 0.077, -0.062], [1.617, -1.294, 0.41, -0.08, 0.836, 0.171]] D: [[1.601, -1.491, 0.468, 0.181, 0.51, -0.093], [0.965, -1.654, 0.463, 0.875, 0.478, 0.252], [1.604, -1.87, -0.185, 0.098, 0.676, 0.612], [1.637, -2.272, -0.12, 0.307, 0.185, 0.124], [1.563, -1.727, 0.204, 0.781, 0.373, 0.021]]
[ "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_101_0.jpg", "./3D-spatial/threeD_Object_Detection/threeD_Object_Detection_101_1.png" ]
B