{"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/rmpe-regional-multi-person-pose-estimation","title":"RMPE: Regional Multi-person Pose Estimation","arxiv_id":"1612.00137","date":"2016-12-01","proceeding":"ICCV 2017 10","authors":["Hao-Shu Fang","Shuqin Xie","Yu-Wing Tai","Cewu Lu"],"abstract":"Multi-person pose estimation in the wild is challenging. Although\nstate-of-the-art human detectors have demonstrated good performance, small\nerrors in localization and recognition are inevitable. These errors can cause\nfailures for a single-person pose estimator (SPPE), especially for methods that\nsolely depend on human detection results. In this paper, we propose a novel\nregional multi-person pose estimation (RMPE) framework to facilitate pose\nestimation in the presence of inaccurate human bounding boxes. Our framework\nconsists of three components: Symmetric Spatial Transformer Network (SSTN),\nParametric Pose Non-Maximum-Suppression (NMS), and Pose-Guided Proposals\nGenerator (PGPG). Our method is able to handle inaccurate bounding boxes and\nredundant detections, allowing it to achieve a 17% increase in mAP over the\nstate-of-the-art methods on the MPII (multi person) dataset.Our model and\nsource codes are publicly available.","url_abs":"http://arxiv.org/abs/1612.00137v5","url_pdf":"http://arxiv.org/pdf/1612.00137v5.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":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/2023-MindSpore-1/ms-code-199","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"mindspore","reach":{"status":"ok"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/Fangyh09/pose_nms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/MVIG-SJTU/RMPE","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"torch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/ManifoldFR/recvis-project","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/MattyChoi/PoseMachines","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/lyqcom/alphapose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"mindspore","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/osmr/imgclsmob","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"mxnet","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/2023-MindSpore-1/ms-code-22","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":{"status":"ok"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/2023-MindSpore-4/Code8/tree/main/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/MVIG-SJTU/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/MindSpore-paper-code-3/code1/tree/main/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":{"status":"ok"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/mindspore-ai/models/tree/master/research/cv/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/yangyucheng000/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":{"status":"ok"}},{"paper_slug":"rmpe-regional-multi-person-pose-estimation","repo_url":"https://github.com/yuanyuanfyy/yycode/tree/mindsporecode/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"2d-human-pose-estimation","task_name":"2D Human Pose Estimation"},{"task_slug":"human-detection","task_name":"Human Detection"},{"task_slug":"keypoint-detection","task_name":"Keypoint Detection"},{"task_slug":"multi-person-pose-estimation","task_name":"Multi-Person Pose Estimation"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[{"method_slug":"spatial-transformer","method_name":"Spatial Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/2d-human-pose-estimation-on-ochuman","task":"2D Human Pose Estimation","dataset":"OCHuman","model":"RMPE","rank_in_archive_order":8,"of":11,"metrics":{"Test AP":"30.7","Validation AP":"38.8"},"uses_additional_data":false},{"leaderboard":"/sota/keypoint-detection-on-coco","task":"Keypoint Detection","dataset":"COCO (Common Objects in Context)","model":"AlphaPose","rank_in_archive_order":11,"of":24,"metrics":{"FPS":"23","Test AP":"73.3"},"uses_additional_data":true},{"leaderboard":"/sota/keypoint-detection-on-coco-test-dev","task":"Keypoint Detection","dataset":"COCO test-dev","model":"AlphaPose","rank_in_archive_order":16,"of":16,"metrics":{"APL":"81.5"},"uses_additional_data":false},{"leaderboard":"/sota/keypoint-detection-on-mpii-multi-person","task":"Keypoint Detection","dataset":"MPII Multi-Person","model":"AlphaPose","rank_in_archive_order":1,"of":9,"metrics":{"mAP@0.5":"82.1%"},"uses_additional_data":false},{"leaderboard":"/sota/keypoint-detection-on-ochuman","task":"Keypoint Detection","dataset":"OCHuman","model":"RMPE","rank_in_archive_order":7,"of":10,"metrics":{"Test AP":"30.7","Validation AP":"38.8"},"uses_additional_data":false},{"leaderboard":"/sota/multi-person-pose-estimation-on-coco-test-dev","task":"Multi-Person Pose Estimation","dataset":"COCO test-dev","model":"RMPE","rank_in_archive_order":15,"of":15,"metrics":{"AP":"61.8","AP50":"83.7","AP75":"69.8","APL":"67.6","APM":"58.6"},"uses_additional_data":false},{"leaderboard":"/sota/multi-person-pose-estimation-on-crowdpose","task":"Multi-Person Pose Estimation","dataset":"CrowdPose","model":"AlphaPose","rank_in_archive_order":21,"of":28,"metrics":{"AP Easy":"71.2","AP Hard":"51.1","AP Medium":"61.4","mAP @0.5:0.95":"61.0"},"uses_additional_data":false},{"leaderboard":"/sota/multi-person-pose-estimation-on-mpii-multi","task":"Multi-Person Pose Estimation","dataset":"MPII Multi-Person","model":"AlphaPose","rank_in_archive_order":1,"of":9,"metrics":{"AP":"82.1%"},"uses_additional_data":false},{"leaderboard":"/sota/pose-estimation-on-coco-test-dev","task":"Pose Estimation","dataset":"COCO test-dev","model":"RMPE++","rank_in_archive_order":27,"of":47,"metrics":{"AP":"72.3","AP50":"89.2","AP75":"79.1","APL":"78.6","APM":"68.0"},"uses_additional_data":false},{"leaderboard":"/sota/pose-estimation-on-coco-test-dev","task":"Pose Estimation","dataset":"COCO test-dev","model":"RMPE","rank_in_archive_order":45,"of":47,"metrics":{"AP":"61.8","AP50":"83.7","AP75":"69.8","APL":"67.6","APM":"58.6"},"uses_additional_data":false},{"leaderboard":"/sota/pose-estimation-on-ochuman","task":"Pose Estimation","dataset":"OCHuman","model":"RMPE","rank_in_archive_order":16,"of":19,"metrics":{"Test AP":"30.7","Validation AP":"38.8"},"uses_additional_data":false},{"leaderboard":"/sota/pose-estimation-on-uav-human","task":"Pose Estimation","dataset":"UAV-Human","model":"AlphaPose","rank_in_archive_order":1,"of":2,"metrics":{"mAP":"56.9"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1612.00137","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}