{"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/resource-aware-person-re-identification","title":"Resource Aware Person Re-identification across Multiple Resolutions","arxiv_id":"1805.08805","date":"2018-05-22","proceeding":"CVPR 2018 6","authors":["Yan Wang","Lequn Wang","Yurong You","Xu Zou","Vincent Chen","Serena Li","Gao Huang","Bharath Hariharan","Kilian Q. Weinberger"],"abstract":"Not all people are equally easy to identify: color statistics might be enough\nfor some cases while others might require careful reasoning about high- and\nlow-level details. However, prevailing person re-identification(re-ID) methods\nuse one-size-fits-all high-level embeddings from deep convolutional networks\nfor all cases. This might limit their accuracy on difficult examples or makes\nthem needlessly expensive for the easy ones. To remedy this, we present a new\nperson re-ID model that combines effective embeddings built on multiple\nconvolutional network layers, trained with deep-supervision. On traditional\nre-ID benchmarks, our method improves substantially over the previous\nstate-of-the-art results on all five datasets that we evaluate on. We then\npropose two new formulations of the person re-ID problem under\nresource-constraints, and show how our model can be used to effectively trade\noff accuracy and computation in the presence of resource constraints. Code and\npre-trained models are available at https://github.com/mileyan/DARENet.","url_abs":"http://arxiv.org/abs/1805.08805v3","url_pdf":"http://arxiv.org/pdf/1805.08805v3.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":"resource-aware-person-re-identification","repo_url":"https://github.com/mileyan/DARENet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"all","task_name":"All"},{"task_slug":"person-re-identification","task_name":"Person Re-Identification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/person-re-identification-on-cuhk03-detected","task":"Person Re-Identification","dataset":"CUHK03 detected","model":"DaRe+RE (CVPR'18)","rank_in_archive_order":12,"of":19,"metrics":{"MAP":"59.0","Rank-1":"63.3"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-cuhk03-labeled","task":"Person Re-Identification","dataset":"CUHK03 labeled","model":"DaRe+RE (CVPR'18)","rank_in_archive_order":14,"of":21,"metrics":{"MAP":"61.6","Rank-1":"66.1"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-dukemtmc-reid","task":"Person Re-Identification","dataset":"DukeMTMC-reID","model":"DaRe(De)+RE+RR [wang2018resource]","rank_in_archive_order":44,"of":94,"metrics":{"Rank-1":"84.4","mAP":"80.0"},"uses_additional_data":false},{"leaderboard":"/sota/person-re-identification-on-market-1501","task":"Person Re-Identification","dataset":"Market-1501","model":"DaRe(De)+RE+RR [wang2018resource]","rank_in_archive_order":91,"of":135,"metrics":{"Rank-1":"90.9","mAP":"86.7"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.08805","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.08805"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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