{"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/sequential-end-to-end-network-for-efficient","title":"Sequential End-to-end Network for Efficient Person Search","arxiv_id":"2103.10148","date":"2021-03-18","proceeding":null,"authors":["Zhengjia Li","Duoqian Miao"],"abstract":"Person search aims at jointly solving Person Detection and Person Re-identification (re-ID). Existing works have designed end-to-end networks based on Faster R-CNN. However, due to the parallel structure of Faster R-CNN, the extracted features come from the low-quality proposals generated by the Region Proposal Network, rather than the detected high-quality bounding boxes. Person search is a fine-grained task and such inferior features will significantly reduce re-ID performance. To address this issue, we propose a Sequential End-to-end Network (SeqNet) to extract superior features. In SeqNet, detection and re-ID are considered as a progressive process and tackled with two sub-networks sequentially. In addition, we design a robust Context Bipartite Graph Matching (CBGM) algorithm to effectively employ context information as an important complementary cue for person matching. Extensive experiments on two widely used person search benchmarks, CUHK-SYSU and PRW, have shown that our method achieves state-of-the-art results. Also, our model runs at 11.5 fps on a single GPU and can be integrated into the existing end-to-end framework easily.","url_abs":"https://arxiv.org/abs/2103.10148v1","url_pdf":"https://arxiv.org/pdf/2103.10148v1.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":"sequential-end-to-end-network-for-efficient","repo_url":"https://github.com/serend1p1ty/SeqNet","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":null,"task_name":"GPU"},{"task_slug":"graph-matching","task_name":"Graph Matching"},{"task_slug":"human-detection","task_name":"Human Detection"},{"task_slug":"person-re-identification","task_name":"Person Re-Identification"},{"task_slug":"person-search","task_name":"Person Search"},{"task_slug":"region-proposal","task_name":"Region Proposal"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"faster-r-cnn","method_name":"Faster R-CNN"},{"method_slug":"rpn","method_name":"RPN"},{"method_slug":"roipool","method_name":"RoIPool"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/person-search-on-cuhk-sysu","task":"Person Search","dataset":"CUHK-SYSU","model":"NAE+SeqNet+CBGM","rank_in_archive_order":8,"of":16,"metrics":{"MAP":"94.8","Top-1":"95.7"},"uses_additional_data":false},{"leaderboard":"/sota/person-search-on-cuhk-sysu","task":"Person Search","dataset":"CUHK-SYSU","model":"OIM+SeqNet+CBGM","rank_in_archive_order":10,"of":16,"metrics":{"MAP":"94.3","Top-1":"95.0"},"uses_additional_data":false},{"leaderboard":"/sota/person-search-on-cuhk-sysu","task":"Person Search","dataset":"CUHK-SYSU","model":"NAE+SeqNet","rank_in_archive_order":12,"of":16,"metrics":{"MAP":"93.8","Top-1":"94.6"},"uses_additional_data":false},{"leaderboard":"/sota/person-search-on-cuhk-sysu","task":"Person Search","dataset":"CUHK-SYSU","model":"OIM+SeqNet","rank_in_archive_order":13,"of":16,"metrics":{"MAP":"93.4","Top-1":"94.1"},"uses_additional_data":false},{"leaderboard":"/sota/person-search-on-prw","task":"Person Search","dataset":"PRW","model":"NAE+SeqNet+CBGM","rank_in_archive_order":8,"of":15,"metrics":{"Top-1":"87.6","mAP":"47.6"},"uses_additional_data":false},{"leaderboard":"/sota/person-search-on-prw","task":"Person Search","dataset":"PRW","model":"NAE+SeqNet","rank_in_archive_order":11,"of":15,"metrics":{"Top-1":"83.4","mAP":"46.7"},"uses_additional_data":false},{"leaderboard":"/sota/person-search-on-prw","task":"Person Search","dataset":"PRW","model":"OIM+SeqNet+CBGM","rank_in_archive_order":12,"of":15,"metrics":{"Top-1":"84.9","mAP":"46.6"},"uses_additional_data":false},{"leaderboard":"/sota/person-search-on-prw","task":"Person Search","dataset":"PRW","model":"OIM+SeqNet","rank_in_archive_order":15,"of":15,"metrics":{"Top-1":"81.7","mAP":"45.8"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2103.10148","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}