Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Improving public datasets markings' quality using unsupervised refinement kernels
LabelMe: A Database and Web-Based Tool for Image Annotation
A codebook-free and annotation-free approach for fine-grained image categorization
Image Segmentation Evaluation: A Survey of Unsupervised Methods
Deep Classifiers from Image Tags in the Wild
Label Refinement Network for Coarse-to-Fine Semantic Segmentation
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
Automating image segmentation verification and validation by learning test oracles
Leveraging the Wisdom of the Crowd for Fine-Grained Recognition
Statistical data cleaning for deep learning of automation tasks from demonstrations
Landmark classification in large-scale image collections
A Dataset for Quality Assessment of Camera Captured Document Images
Identifying Mislabeled Training Data
FeaBoost: Joint Feature and Label Refinement for Semantic Segmentation.
World-wide scale geotagged image dataset for automatic image annotation and reverse geotagging
MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features
Annotating photo collections by label propagation according to multiple similarity cues
LabelBank: Revisiting Global Perspectives for Semantic Segmentation
KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing
Evaluating approaches for supervised semantic labeling
Gated Feedback Refinement Network for Dense Image Labeling
An Integrated Approach of Automatic Road Extraction and Evaluation From Remotely Sensed Imagery
A Fitts Law comparison of eye tracking and manual input in the selection of visual targets
Calibration of a MEMS inertial measurement unit
Social software and participatory learning: Pedagogical choices with technology affordances in the Web 2.0 era
Why is Real-World Visual Object Recognition Hard?