{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/maskcl-semantic-mask-driven-contrastive","title":"SiCL: Silhouette-Driven Contrastive Learning for Unsupervised Person Re-Identification with Clothes Change","arxiv_id":"2305.13600","date":"2023-05-23","proceeding":null,"authors":["Mingkun Li","Peng Xu","Chun-Guang Li","Jun Guo"],"abstract":"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.","url_abs":"https://arxiv.org/abs/2305.13600v2","url_pdf":"https://arxiv.org/pdf/2305.13600v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"maskcl-semantic-mask-driven-contrastive","repo_url":"https://github.com/MingkunLishigure/MaskCL","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"clothes-changing-person-re-identification","task_name":"Clothes Changing Person Re-Identification"},{"task_slug":"contrastive-learning","task_name":"Contrastive Learning"},{"task_slug":"person-re-identification","task_name":"Person Re-Identification"},{"task_slug":null,"task_name":"Unsupervised Clothes Changing Person Re-Identification"},{"task_slug":"unsupervised-long-term-person-re","task_name":"Unsupervised Long Term Person Re-Identification"},{"task_slug":"unsupervised-person-re-identification","task_name":"Unsupervised Person Re-Identification"}],"methods":[{"method_slug":"contrastive-learning","method_name":"Contrastive Learning"},{"method_slug":"fail","method_name":"fail"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/unsupervised-person-re-identification-on-ltcc","task":"Unsupervised Person Re-Identification","dataset":"LTCC","model":"MaskCL","rank_in_archive_order":1,"of":1,"metrics":{"Rank-1":"20.7","mAP":"10.1"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-person-re-identification-on-prcc","task":"Unsupervised Person Re-Identification","dataset":"PRCC","model":"SiCL","rank_in_archive_order":1,"of":1,"metrics":{"Rank-1":"43.2","mAP":"55.4"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-person-re-identification-on-vc","task":"Unsupervised Person Re-Identification","dataset":"VC-Clothes","model":"SiCL","rank_in_archive_order":1,"of":1,"metrics":{"Rank-1":"71.7","mAP":"63.9"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2305.13600","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}