Progressive spatial–temporal transfer model for unsupervised person re-identification
Author:
Funder
Humanities and Social Sciences Planning Fund Projects of Ministry of Education of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13735-024-00324-w.pdf
Reference66 articles.
1. Barz B, Rodner E, Garcia YG, Denzler J (2018) Detecting regions of maximal divergence for spatio-temporal anomaly detection. IEEE Trans Pattern Anal Mach Intell 41:1088–1101
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3. Chen L, Yang H, Gao Z (2019) Joint attentive spatial–temporal feature aggregation for video-based person re-identification. IEEE Access 7:41230–41240
4. Chen P, Liu W, Dai P, Liu J, Ye Q, Xu M, Chen Q, Ji R (2021b) Occlude them all: occlusion-aware attention network for occluded person re-id. In: Proceedings of the IEEE/CVF international conference on computer vision, pp 11833–11842
5. Cho Y, Kim W.J, Hong S, Yoon SE (2022) Part-based pseudo label refinement for unsupervised person re-identification. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 7308–7318
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