Joint Detection and Identification Feature Learning for Person Search

@article{Xiao2017JointDA,
  title={Joint Detection and Identification Feature Learning for Person Search},
  author={Tong Xiao and Shuang Li and Bochao Wang and Liang Lin and Xiaogang Wang},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={3376-3385}
}
Existing person re-identification benchmarks and methods mainly focus on matching cropped pedestrian images between queries and candidates. However, it is different from real-world scenarios where the annotations of pedestrian bounding boxes are unavailable and the target person needs to be searched from a gallery of whole scene images. To close the gap, we propose a new deep learning framework for person search. Instead of breaking it down into two separate tasks—pedestrian detection… CONTINUE READING
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