{"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/multi-person-absolute-3d-human-pose","title":"Multi-Person Absolute 3D Human Pose Estimation with Weak Depth Supervision","arxiv_id":"2004.03989","date":"2020-04-08","proceeding":null,"authors":["Marton Veges","Andras Lorincz"],"abstract":"In 3D human pose estimation one of the biggest problems is the lack of large, diverse datasets. This is especially true for multi-person 3D pose estimation, where, to our knowledge, there are only machine generated annotations available for training. To mitigate this issue, we introduce a network that can be trained with additional RGB-D images in a weakly supervised fashion. Due to the existence of cheap sensors, videos with depth maps are widely available, and our method can exploit a large, unannotated dataset. Our algorithm is a monocular, multi-person, absolute pose estimator. We evaluate the algorithm on several benchmarks, showing a consistent improvement in error rates. Also, our model achieves state-of-the-art results on the MuPoTS-3D dataset by a considerable margin.","url_abs":"https://arxiv.org/abs/2004.03989v1","url_pdf":"https://arxiv.org/pdf/2004.03989v1.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":"multi-person-absolute-3d-human-pose","repo_url":"https://github.com/vegesm/wdspose","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"3d-human-pose-estimation","task_name":"3D Human Pose Estimation"},{"task_slug":"3d-multi-person-pose-estimation-absolute","task_name":"3D Multi-Person Pose Estimation (absolute)"},{"task_slug":"3d-multi-person-pose-estimation-root-relative","task_name":"3D Multi-Person Pose Estimation (root-relative)"},{"task_slug":"3d-pose-estimation","task_name":"3D Pose Estimation"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/3d-multi-person-pose-estimation-absolute-on","task":"3D Multi-Person Pose Estimation (absolute)","dataset":"MuPoTS-3D","model":"WDSPose","rank_in_archive_order":9,"of":14,"metrics":{"3DPCK":"37.3"},"uses_additional_data":false},{"leaderboard":"/sota/3d-multi-person-pose-estimation-root-relative","task":"3D Multi-Person Pose Estimation (root-relative)","dataset":"MuPoTS-3D","model":"WDSPose","rank_in_archive_order":10,"of":20,"metrics":{"3DPCK":"82.7"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2004.03989","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}