{"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/enhancing-person-re-identification-via","title":"Enhancing person re-identification via Uncertainty Feature Fusion Method and Auto-weighted Measure Combination","arxiv_id":"2405.01101","date":"2024-05-02","proceeding":"Knowledge-Based Systems 2024 11","authors":["Quang-Huy Che","Le-Chuong Nguyen","Duc-Tuan Luu","Vinh-Tiep Nguyen"],"abstract":"Person re-identification (Re-ID) is a challenging task that involves identifying the same person across different camera views in surveillance systems. Current methods usually rely on features from single-camera views, which can be limiting when dealing with multiple cameras and challenges such as changing viewpoints and occlusions. In this paper, a new approach is introduced that enhances the capability of ReID models through the Uncertain Feature Fusion Method (UFFM) and Auto-weighted Measure Combination (AMC). UFFM generates multi-view features using features extracted independently from multiple images to mitigate view bias. However, relying only on similarity based on multi-view features is limited because these features ignore the details represented in single-view features. Therefore, we propose the AMC method to generate a more robust similarity measure by combining various measures. Our method significantly improves Rank@1 accuracy and Mean Average Precision (mAP) when evaluated on person re-identification datasets. Combined with the BoT Baseline on challenging datasets, we achieve impressive results, with a 7.9% improvement in Rank@1 and a 12.1% improvement in mAP on the MSMT17 dataset. On the Occluded-DukeMTMC dataset, our method increases Rank@1 by 22.0% and mAP by 18.4%. Code is available: https://github.com/chequanghuy/Enhancing-Person-Re-Identification-via-UFFM-and-AMC","url_abs":"https://arxiv.org/abs/2405.01101v5","url_pdf":"https://arxiv.org/pdf/2405.01101v5.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":"enhancing-person-re-identification-via","repo_url":"https://github.com/chequanghuy/Enhancing-Person-Re-Identification-via-UFFM-and-AMC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"person-re-identification","task_name":"Person Re-Identification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/person-re-identification-on-dukemtmc-reid","task":"Person Re-Identification","dataset":"DukeMTMC-reID","model":"CLIP-ReID Baseline+UFFM+AMC","rank_in_archive_order":22,"of":94,"metrics":{"Rank-1":"91.3","mAP":"85.0"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-msmt17","task":"Person Re-Identification","dataset":"MSMT17","model":"CLIP-ReID Baseline + UFFM +AMC","rank_in_archive_order":18,"of":43,"metrics":{"Rank-1":"83.8","mAP":"67.6"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-msmt17","task":"Person Re-Identification","dataset":"MSMT17","model":"BoT+UFFM+AMC","rank_in_archive_order":28,"of":43,"metrics":{"Rank-1":"82.0","mAP":"62.3"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-market-1501","task":"Person Re-Identification","dataset":"Market-1501","model":"SOLIDER +UFFM+AMC","rank_in_archive_order":4,"of":135,"metrics":{"Rank-1":"97","mAP":"94.9"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-market-1501","task":"Person Re-Identification","dataset":"Market-1501","model":"BoT+UFFM+AMC","rank_in_archive_order":20,"of":135,"metrics":{"Rank-1":"96.2","mAP":"91.0"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-market-1501","task":"Person Re-Identification","dataset":"Market-1501","model":"CLIP-ReID Baseline +UFFM+AMC","rank_in_archive_order":28,"of":135,"metrics":{"Rank-1":"96.1","mAP":"92.0"},"uses_additional_data":true},{"leaderboard":"/sota/person-re-identification-on-occluded-dukemtmc","task":"Person Re-Identification","dataset":"Occluded-DukeMTMC","model":"CLIPReID-Baseline+UFFM+AMC","rank_in_archive_order":31,"of":32,"metrics":{"mAP":"61.9"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-occluded-dukemtmc","task":"Person Re-Identification","dataset":"Occluded-DukeMTMC","model":"BoT+UFFM+AMC","rank_in_archive_order":32,"of":32,"metrics":{"mAP":"61.0"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}