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Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
Among the components of a pedestrian detector, its trained pedestrian classifier is crucial for achieving the desired performance. The initial task of the training process consists in collecting samples of pedestrians and background, which involves tiresome manual annotation of pedestrian bounding boxes (BBs). Thus, recent works have assessed the use of automatically collected samples from photo-realistic virtual worlds. However, learning from virtual-world samples and testing in real-world
doi:10.1109/cvprw.2013.107
dblp:conf/cvpr/VazquezXRLP13
fatcat:5b657dmquvbcpdhyg6wyuk4r6y