{"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/fast-and-accurate-person-re-identification","title":"Fast and Accurate Person Re-Identification with RMNet","arxiv_id":"1812.02465","date":"2018-12-06","proceeding":null,"authors":["Evgeny Izutov"],"abstract":"In this paper we introduce a new neural network architecture designed to use\nin embedded vision applications. It merges the best working practices of\nnetwork architectures like MobileNets and ResNets to our named RMNet\narchitecture. We also focus on key moments of building mobile architectures to\ncarry out in the limited computation budget. Additionally, to demonstrate the\neffectiveness of our architecture we evaluate the RMNet backbone on Person\nRe-identification task. The proposed approach is in top 3 of state of the art\nsolutions on Market-1501 challenge, however our method significantly\noutperforms them by the inference speed.","url_abs":"http://arxiv.org/abs/1812.02465v1","url_pdf":"http://arxiv.org/pdf/1812.02465v1.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":"fast-and-accurate-person-re-identification","repo_url":"https://github.com/TallyH0/aihubpedkorean","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"person-re-identification","task_name":"Person Re-Identification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}