Group-aware Label Transfer for Domain Adaptive Person Re-identification

@article{Zheng2021GroupawareLT,
  title={Group-aware Label Transfer for Domain Adaptive Person Re-identification},
  author={Kecheng Zheng and Wu Liu and Lingxiao He and Tao Mei and Jiebo Luo and Zhengjun Zha},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021},
  pages={5306-5315}
}
  • Kecheng ZhengWu Liu Zhengjun Zha
  • Published 23 March 2021
  • Computer Science
  • 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Unsupervised Domain Adaptive (UDA) person re-identification (ReID) aims at adapting the model trained on a labeled source-domain dataset to a target-domain dataset without any further annotations. Most successful UDA-ReID approaches combine clustering-based pseudo-label prediction with representation learning and perform the two steps in an alternating fashion. However, offline interaction between these two steps may allow noisy pseudo labels to substantially hinder the capability of the model… 

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