{"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/person-re-identification-past-present-and","title":"Person Re-identification: Past, Present and Future","arxiv_id":"1610.02984","date":"2016-10-10","proceeding":null,"authors":["Liang Zheng","Yi Yang","Alexander G. Hauptmann"],"abstract":"Person re-identification (re-ID) has become increasingly popular in the\ncommunity due to its application and research significance. It aims at spotting\na person of interest in other cameras. In the early days, hand-crafted\nalgorithms and small-scale evaluation were predominantly reported. Recent years\nhave witnessed the emergence of large-scale datasets and deep learning systems\nwhich make use of large data volumes. Considering different tasks, we classify\nmost current re-ID methods into two classes, i.e., image-based and video-based;\nin both tasks, hand-crafted and deep learning systems will be reviewed.\nMoreover, two new re-ID tasks which are much closer to real-world applications\nare described and discussed, i.e., end-to-end re-ID and fast re-ID in very\nlarge galleries. This paper: 1) introduces the history of person re-ID and its\nrelationship with image classification and instance retrieval; 2) surveys a\nbroad selection of the hand-crafted systems and the large-scale methods in both\nimage- and video-based re-ID; 3) describes critical future directions in\nend-to-end re-ID and fast retrieval in large galleries; and 4) finally briefs\nsome important yet under-developed issues.","url_abs":"http://arxiv.org/abs/1610.02984v1","url_pdf":"http://arxiv.org/pdf/1610.02984v1.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":[],"tasks":[{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"person-re-identification","task_name":"Person Re-Identification"},{"task_slug":"retrieval","task_name":"Retrieval"},{"task_slug":"image-classification","task_name":"image-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/person-re-identification-on-dukemtmc-reid","task":"Person Re-Identification","dataset":"DukeMTMC-reID","model":"IDE","rank_in_archive_order":87,"of":94,"metrics":{"Rank-1":"65.22","mAP":"44.99"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-market-1501","task":"Person Re-Identification","dataset":"Market-1501","model":"IDE","rank_in_archive_order":116,"of":135,"metrics":{"Rank-1":"72.54","mAP":"46.00"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1610.02984","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}