Push for Center Learning via Orthogonalization and Subspace Masking for Person Re-Identification

@article{Wang2021PushFC,
  title={Push for Center Learning via Orthogonalization and Subspace Masking for Person Re-Identification},
  author={Weinong Wang and Wenjie Pei and Qiong Cao and Shu Liu and Guangming Lu and Yu-Wing Tai},
  journal={IEEE Transactions on Image Processing},
  year={2021},
  volume={30},
  pages={907-920}
}
Person re-identification aims to identify whether pairs of images belong to the same person or not. This problem is challenging due to large differences in camera views, lighting and background. One of the mainstream in learning CNN features is to design loss functions which reinforce both the class separation and intra-class compactness. In this paper, we propose a novel Orthogonal Center Learning method with Subspace Masking for person re-identification. We make the following contributions: 1… Expand
2 Citations
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