Feature Erasing and Diffusion Network for Occluded Person Re-Identification

@article{Wang2021FeatureEA,
  title={Feature Erasing and Diffusion Network for Occluded Person Re-Identification},
  author={Zhikang Wang and Feng Zhu and Shixiang Tang and Rui Zhao and Lihuo He and Jiangning Song},
  journal={2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021},
  pages={4744-4753}
}
Occluded person re-identification (ReID) aims at matching occluded person images to holistic ones across different camera views. Target Pedestrians (TP) are often disturbed by Non-Pedestrian Occlusions (NPO) and Non-Target Pedestrians (NTP). Previous methods mainly focus on increasing the model's robustness against NPO while ignoring feature contamination from NTP. In this paper, we propose a novel Feature Erasing and Diffusion Network (FED) to simultaneously handle challenges from NPO and NTP… 

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