{"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/gated-siamese-convolutional-neural-network","title":"Gated Siamese Convolutional Neural Network Architecture for Human Re-Identification","arxiv_id":"1607.08378","date":"2016-07-28","proceeding":null,"authors":["Rahul Rama Varior","Mrinal Haloi","Gang Wang"],"abstract":"Matching pedestrians across multiple camera views, known as human\nre-identification, is a challenging research problem that has numerous\napplications in visual surveillance. With the resurgence of Convolutional\nNeural Networks (CNNs), several end-to-end deep Siamese CNN architectures have\nbeen proposed for human re-identification with the objective of projecting the\nimages of similar pairs (i.e. same identity) to be closer to each other and\nthose of dissimilar pairs to be distant from each other. However, current\nnetworks extract fixed representations for each image regardless of other\nimages which are paired with it and the comparison with other images is done\nonly at the final level. In this setting, the network is at risk of failing to\nextract finer local patterns that may be essential to distinguish positive\npairs from hard negative pairs. In this paper, we propose a gating function to\nselectively emphasize such fine common local patterns by comparing the\nmid-level features across pairs of images. This produces flexible\nrepresentations for the same image according to the images they are paired\nwith. We conduct experiments on the CUHK03, Market-1501 and VIPeR datasets and\ndemonstrate improved performance compared to a baseline Siamese CNN\narchitecture.","url_abs":"http://arxiv.org/abs/1607.08378v2","url_pdf":"http://arxiv.org/pdf/1607.08378v2.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":"person-re-identification","task_name":"Person Re-Identification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/person-re-identification-on-market-1501","task":"Person Re-Identification","dataset":"Market-1501","model":"S-CNN","rank_in_archive_order":119,"of":135,"metrics":{"Rank-1":"65.88","mAP":"39.55"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1607.08378","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}