MCFR: multi-confidence contrastive learning with feature refined for unsupervised person re-identification

Wanru Peng; Houjin Chen; Yanfeng Li; Jia Sun

doi:10.1007/s00371-023-02890-2

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MCFR: multi-confidence contrastive learning with feature refined for unsupervised person re-identification

Wanru Peng Houjin Chen Yanfeng Li Jia Sun

Year: 2023 Journal: The Visual Computer Vol: 40 (3)Pages: 1853-1866 Publisher: Springer Science+Business Media

DOI: 10.1007/s00371-023-02890-2

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Keywords:

Discriminative model Computer science Artificial intelligence Benchmark (surveying) Feature learning Outlier Feature (linguistics) Machine learning Pattern recognition (psychology) Identification (biology) Similarity (geometry) Unsupervised learning Image (mathematics)

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Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Gait Recognition and Analysis

Physical Sciences → Engineering → Biomedical Engineering

Human Pose and Action Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

MCFR: multi-confidence contrastive learning with feature refined for unsupervised person re-identification

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