A comprehensive survey of visible infrared person re-identification from an application perspective-Reference-Cited by-同舟云学术

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A comprehensive survey of visible infrared person re-identification from an application perspective

Published:2024-04-24 Issue: Volume: Page:
ISSN:1573-7721
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Chang Hua,Xu Xin,Liu Wei,Lu Lingyi,Li Weigang

Funder

National Natural Science Foundation of China

University-level Student Innovation and Entrepreneurship Training Program

Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11042-024-19196-7.pdf

Reference87 articles.

1. Wu A, Zheng W-S, Yu H-X, Gong S, Lai, J (2017) RGB-infrared cross-modality person re-identification. In: Proceedings of the IEEE/CVF International conference on computer vision. IEEE, Venice, Italy, pp 5380–5389

2. Wang Z, Wang Z, Zheng Y, Wu Y, Zeng W, Satoh S (2019) Beyond intra-modality: a survey of heterogeneous person re-identification. arXiv:1905.10048, https://doi.org/10.48550/arXiv.1905.10048

3. Leng Q, Ye M, Tian Q (2019) A survey of open-world person re-identification. IEEE Trans Circ Syst Video Technol 30(4):1092–1108. https://doi.org/10.1109/TCSVT.2019.2898940

4. Ye M, Shen J, Lin G, Xiang T, Shao L, Hoi SC (2021) Deep learning for person re-identification: a survey and outlook. IEEE Trans Pattern Anal Mach Intell 44(6):2872–2893. https://doi.org/10.1109/TPAMI.2021.3054775

5. Huang N, Liu J, Miao Y, Zhang Q, Han J (2023) Deep learning for visible-infrared cross-modality person re-identification: a comprehensive review. Inf Fusion 91(16):396–411. https://doi.org/10.1016/j.inffus.2022.10.024

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