Papers › SiCL: Silhouette-Driven Contrastive Learning for Unsupervised Person Re-Identification...
SiCL: Silhouette-Driven Contrastive Learning for Unsupervised Person Re-Identification with Clothes Change
Mingkun Li, Peng Xu, Chun-Guang Li, Jun Guo
In this paper, we address a highly challenging yet critical task: unsupervised long-term person re-identification with clothes change. Existing unsupervised person re-id methods are mainly designed for short-term scenarios and usually rely on RGB cues so that fail to perceive feature patterns that are independent of the clothes. To crack this bottleneck, we propose a silhouette-driven contrastive learning (SiCL) method, which is designed to learn cross-clothes invariance by integrating both the RGB cues and the silhouette information within a contrastive learning framework. To our knowledge, this is the first tailor-made framework for unsupervised long-term clothes change \reid{}, with superior performance on six benchmark datasets. We conduct extensive experiments to evaluate our proposed SiCL compared to the state-of-the-art unsupervised person reid methods across all the representative datasets. Experimental results demonstrate that our proposed SiCL significantly outperforms other unsupervised re-id methods.
In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
1 archive task tag without a task page not shown.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Unsupervised Person Re-Identification | LTCC | MaskCL | Rank-1 | 20.7 | #1 of 1 | Archive leaderboard | report |
| Unsupervised Person Re-Identification | LTCC | MaskCL | mAP | 10.1 | #1 of 1 | Archive leaderboard | report |
| Unsupervised Person Re-Identification | PRCC | SiCL | Rank-1 | 43.2 | #1 of 1 | Archive leaderboard | report |
| Unsupervised Person Re-Identification | PRCC | SiCL | mAP | 55.4 | #1 of 1 | Archive leaderboard | report |
| Unsupervised Person Re-Identification | VC-Clothes | SiCL | Rank-1 | 71.7 | #1 of 1 | Archive leaderboard | report |
| Unsupervised Person Re-Identification | VC-Clothes | SiCL | mAP | 63.9 | #1 of 1 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections