{"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/a-systematic-evaluation-and-benchmark-for","title":"A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets","arxiv_id":"1605.09653","date":"2016-05-31","proceeding":null,"authors":["Srikrishna Karanam","Mengran Gou","Ziyan Wu","Angels Rates-Borras","Octavia Camps","Richard J. Radke"],"abstract":"Person re-identification (re-id) is a critical problem in video analytics\napplications such as security and surveillance. The public release of several\ndatasets and code for vision algorithms has facilitated rapid progress in this\narea over the last few years. However, directly comparing re-id algorithms\nreported in the literature has become difficult since a wide variety of\nfeatures, experimental protocols, and evaluation metrics are employed. In order\nto address this need, we present an extensive review and performance evaluation\nof single- and multi-shot re-id algorithms. The experimental protocol\nincorporates the most recent advances in both feature extraction and metric\nlearning. To ensure a fair comparison, all of the approaches were implemented\nusing a unified code library that includes 11 feature extraction algorithms and\n22 metric learning and ranking techniques. All approaches were evaluated using\na new large-scale dataset that closely mimics a real-world problem setting, in\naddition to 16 other publicly available datasets: VIPeR, GRID, CAVIAR,\nDukeMTMC4ReID, 3DPeS, PRID, V47, WARD, SAIVT-SoftBio, CUHK01, CHUK02, CUHK03,\nRAiD, iLIDSVID, HDA+ and Market1501. The evaluation codebase and results will\nbe made publicly available for community use.","url_abs":"http://arxiv.org/abs/1605.09653v5","url_pdf":"http://arxiv.org/pdf/1605.09653v5.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":"a-systematic-evaluation-and-benchmark-for","repo_url":"https://github.com/RSL-NEU/person-reid-benchmark","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"a-systematic-evaluation-and-benchmark-for","repo_url":"https://github.com/HoYoung1/image-embedding","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"metric-learning","task_name":"Metric Learning"},{"task_slug":"person-re-identification","task_name":"Person Re-Identification"}],"methods":[],"datasets_introduced":[{"slug":"airport","name":"Airport","full_name":"Airport"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1605.09653","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}