{"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/fpb-feature-pyramid-branch-for-person-re","title":"FPB: Feature Pyramid Branch for Person Re-Identification","arxiv_id":"2108.01901","date":"2021-08-04","proceeding":null,"authors":["Suofei Zhang","Zirui Yin","Xiofu Wu","Kun Wang","Quan Zhou","Bin Kang"],"abstract":"High performance person Re-Identification (Re-ID) requires the model to focus on both global silhouette and local details of pedestrian. To extract such more representative features, an effective way is to exploit deep models with multiple branches. However, most multi-branch based methods implemented by duplication of part backbone structure normally lead to severe increase of computational cost. In this paper, we propose a lightweight Feature Pyramid Branch (FPB) to extract features from different layers of networks and aggregate them in a bidirectional pyramid structure. Cooperated by attention modules and our proposed cross orthogonality regularization, FPB significantly prompts the performance of backbone network by only introducing less than 1.5M extra parameters. Extensive experimental results on standard benchmark datasets demonstrate that our proposed FPB based model outperforms state-of-the-art methods with obvious margin as well as much less model complexity. FPB borrows the idea of the Feature Pyramid Network (FPN) from prevailing object detection methods. To our best knowledge, it is the first successful application of similar structure in person Re-ID tasks, which empirically proves that pyramid network as affiliated branch could be a potential structure in related feature embedding models. The source code is publicly available at https://github.com/anocodetest1/FPB.git.","url_abs":"https://arxiv.org/abs/2108.01901v1","url_pdf":"https://arxiv.org/pdf/2108.01901v1.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":"fpb-feature-pyramid-branch-for-person-re","repo_url":"https://github.com/anocodetest1/FPB","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"person-re-identification","task_name":"Person Re-Identification"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/person-re-identification-on-cuhk03-labeled","task":"Person Re-Identification","dataset":"CUHK03 labeled","model":"FPB","rank_in_archive_order":6,"of":21,"metrics":{"MAP":"83.8","Rank-1":"85.9"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-dukemtmc-reid","task":"Person Re-Identification","dataset":"DukeMTMC-reID","model":"FPB","rank_in_archive_order":29,"of":94,"metrics":{"Rank-1":"91.2","mAP":"82.9"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-market-1501","task":"Person Re-Identification","dataset":"Market-1501","model":"FPB","rank_in_archive_order":30,"of":135,"metrics":{"Rank-1":"96.1","mAP":"90.6"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2108.01901","atlas_url":"https://app.syntology.ai/?focus=2108.01901","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}