{"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/cloth-changing-person-re-identification-from","title":"Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization","arxiv_id":"2103.15537","date":"2021-03-29","proceeding":"CVPR 2022 1","authors":["Xin Jin","Tianyu He","Kecheng Zheng","Zhiheng Yin","Xu Shen","Zhen Huang","Ruoyu Feng","Jianqiang Huang","Xian-Sheng Hua","Zhibo Chen"],"abstract":"Cloth-Changing person re-identification (CC-ReID) aims at matching the same person across different locations over a long-duration, e.g., over days, and therefore inevitably meets challenge of changing clothing. In this paper, we focus on handling well the CC-ReID problem under a more challenging setting, i.e., just from a single image, which enables high-efficiency and latency-free pedestrian identify for real-time surveillance applications. Specifically, we introduce Gait recognition as an auxiliary task to drive the Image ReID model to learn cloth-agnostic representations by leveraging personal unique and cloth-independent gait information, we name this framework as GI-ReID. GI-ReID adopts a two-stream architecture that consists of a image ReID-Stream and an auxiliary gait recognition stream (Gait-Stream). The Gait-Stream, that is discarded in the inference for high computational efficiency, acts as a regulator to encourage the ReID-Stream to capture cloth-invariant biometric motion features during the training. To get temporal continuous motion cues from a single image, we design a Gait Sequence Prediction (GSP) module for Gait-Stream to enrich gait information. Finally, a high-level semantics consistency over two streams is enforced for effective knowledge regularization. Experiments on multiple image-based Cloth-Changing ReID benchmarks, e.g., LTCC, PRCC, Real28, and VC-Clothes, demonstrate that GI-ReID performs favorably against the state-of-the-arts. Codes are available at https://github.com/jinx-USTC/GI-ReID.","url_abs":"https://arxiv.org/abs/2103.15537v4","url_pdf":"https://arxiv.org/pdf/2103.15537v4.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":"cloth-changing-person-re-identification-from","repo_url":"https://github.com/jinx-USTC/GI-ReID","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"cloth-changing-person-re-identification","task_name":"Cloth-Changing Person Re-Identification"},{"task_slug":"computational-efficiency","task_name":"Computational Efficiency"},{"task_slug":"gait-recognition","task_name":"Gait Recognition"},{"task_slug":"person-re-identification","task_name":"Person Re-Identification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/person-re-identification-on-ltcc","task":"Person Re-Identification","dataset":"LTCC","model":"GI-ReID","rank_in_archive_order":11,"of":13,"metrics":{" Rank-1":"27.3"," mAP":"10.4"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-mars","task":"Person Re-Identification","dataset":"MARS","model":"Baseline + GS + SC (ours)","rank_in_archive_order":13,"of":21,"metrics":{"Rank-1":"88.32","mAP":"80.41"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-prcc","task":"Person Re-Identification","dataset":"PRCC","model":"GI-ReID","rank_in_archive_order":13,"of":13,"metrics":{" Rank-1":"33.3"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-vc-clothes","task":"Person Re-Identification","dataset":"VC-Clothes","model":"GI-ReID","rank_in_archive_order":6,"of":6,"metrics":{" Rank-1":"64.5","mAP":"57.8"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2103.15537","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}