An adaptive self-correction joint training framework for person re-identification with noisy labels

Author:

Fu HuiORCID,Zhang Ke,Wang JingyuORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference52 articles.

1. Robust bi-tempered logistic loss based on bregman divergences;Amid;Advances in Neural Information Processing Systems,2019

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3. Understanding and improving early stopping for learning with noisy labels;Bai;Advances in Neural Information Processing Systems,2021

4. Chen, W., Chen, X., Zhang, J., & Huang, K. (2017). Beyond triplet loss: A deep quadruplet network for person re-identification. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 403–412).

5. Chen, T., Ding, S., Xie, J., Yuan, Y., Chen, W., Yang, Y., et al. (2019). Abd-net: Attentive but diverse person re-identification. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 8351–8361).

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