Confidence-adapted meta-interaction for unsupervised person re-identification
Author:
Funder
the National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-023-04863-3.pdf
Reference49 articles.
1. Karanam S, Gou M, Wu Z, Rates-Borras A, Camps OI, Radke RJ (2019) A systematic evaluation and benchmark for person re-identification: Features, metrics, and datasets. IEEE Transactions on Pattern Analysis and Machine Intelligence 41(3):523–536
2. Song W, Zheng J, Wu Y, Chen C, Liu F (2021) Discriminative feature extraction for video person re-identification via multi-task network. Appl Intell 51(2):788–803
3. Pang Z, Guo J, Sun W, Xiao Y, Ming Yu (2022) Cross-domain person re-identification by hybrid supervised and unsupervised learning. Appl Intell 52(3):2987–3001
4. Ristani E, Solera F, Zou R, Cucchiara R, Tomasi C (2016) Performance measures and a data set for multi-target, multi-camera tracking. In European conference on computer vision. Springer, pp 17–35
5. Zheng L, Bie Z, Sun Y, Wang J, Su C, Wang S, Tian Q (2016) Mars: A video benchmark for large-scale person re-identification. In European Conference on Computer Vision. Springer, pp 868–884
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