Patch-based tendency camera multi-constraint learning for unsupervised person re-identification-Reference-Cited by-同舟云学术

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Patch-based tendency camera multi-constraint learning for unsupervised person re-identification

Published:2024-05 Issue: Volume:101 Page:104180
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Tao Xuefeng,Kong Jun,Jiang Min,Luo Xi,Liu Tianshan

Funder

Higher Education Discipline Innovation Project

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Foundation for Innovative Research Groups of the National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Reference44 articles.

1. C. Wu, W. Ge, A. Wu, X. Chang, Camera-conditioned stable feature generation for isolated camera supervised person re-identification, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 20238–20248.

2. Multiscale global-aware channel attention for person re-identification;Zhu;J. Vis. Commun. Image Represent.,2023

3. Person re-identification based on deep learning — an overview;Wei;J. Vis. Commun. Image Represent.,2022

4. Y. Lin, X. Dong, L. Zheng, Y. Yan, Y. Yang, A bottom-up clustering approach to unsupervised person re-identification, in: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 33, 2019, pp. 8738–8745.

5. Hsp-mfl: A high-level semantic property driven multi-task feature learning network for unsupervised person re-id;Zhao;J. Vis. Commun. Image Represent.,2023

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