{"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/alphapose-whole-body-regional-multi-person","title":"AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time","arxiv_id":"2211.03375","date":"2022-11-07","proceeding":null,"authors":["Hao-Shu Fang","Jiefeng Li","Hongyang Tang","Chao Xu","Haoyi Zhu","Yuliang Xiu","Yong-Lu Li","Cewu Lu"],"abstract":"Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision. To capture the subtle actions of humans for complex behavior analysis, whole-body pose estimation including the face, body, hand and foot is essential over conventional body-only pose estimation. In this paper, we present AlphaPose, a system that can perform accurate whole-body pose estimation and tracking jointly while running in realtime. To this end, we propose several new techniques: Symmetric Integral Keypoint Regression (SIKR) for fast and fine localization, Parametric Pose Non-Maximum-Suppression (P-NMS) for eliminating redundant human detections and Pose Aware Identity Embedding for jointly pose estimation and tracking. During training, we resort to Part-Guided Proposal Generator (PGPG) and multi-domain knowledge distillation to further improve the accuracy. Our method is able to localize whole-body keypoints accurately and tracks humans simultaneously given inaccurate bounding boxes and redundant detections. We show a significant improvement over current state-of-the-art methods in both speed and accuracy on COCO-wholebody, COCO, PoseTrack, and our proposed Halpe-FullBody pose estimation dataset. Our model, source codes and dataset are made publicly available at https://github.com/MVIG-SJTU/AlphaPose.","url_abs":"https://arxiv.org/abs/2211.03375v1","url_pdf":"https://arxiv.org/pdf/2211.03375v1.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":"alphapose-whole-body-regional-multi-person","repo_url":"https://github.com/MVIG-SJTU/AlphaPose","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"alphapose-whole-body-regional-multi-person","repo_url":"https://github.com/fang-haoshu/halpe-fullbody","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"alphapose-whole-body-regional-multi-person","repo_url":"https://github.com/smartadpole/spider","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"alphapose-whole-body-regional-multi-person","repo_url":"https://github.com/2023-MindSpore-1/ms-code-16/tree/main/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"alphapose-whole-body-regional-multi-person","repo_url":"https://github.com/2024-MindSpore-1/Code5/tree/main/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"alphapose-whole-body-regional-multi-person","repo_url":"https://github.com/2024-MindSpore-1/Code6/tree/main/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"alphapose-whole-body-regional-multi-person","repo_url":"https://github.com/MindSpore-paper-code-3/code6/tree/main/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"alphapose-whole-body-regional-multi-person","repo_url":"https://github.com/code-implementation1/Code2/tree/main/AlphaPose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"knowledge-distillation","task_name":"Knowledge Distillation"},{"task_slug":"multi-person-pose-estimation","task_name":"Multi-Person Pose Estimation"},{"task_slug":"multi-person-pose-estimation-and-tracking","task_name":"Multi-Person Pose Estimation and Tracking"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[{"method_slug":"aware","method_name":"AWARE"},{"method_slug":"knowledge-distillation","method_name":"Knowledge Distillation"},{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[{"slug":"halpe-fullbody","name":"Halpe-FullBody","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2211.03375","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}