{"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/3d-human-pose-estimation-in-rgbd-images-for","title":"3D Human Pose Estimation in RGBD Images for Robotic Task Learning","arxiv_id":"1803.02622","date":"2018-03-07","proceeding":null,"authors":["Christian Zimmermann","Tim Welschehold","Christian Dornhege","Wolfram Burgard","Thomas Brox"],"abstract":"We propose an approach to estimate 3D human pose in real world units from a\nsingle RGBD image and show that it exceeds performance of monocular 3D pose\nestimation approaches from color as well as pose estimation exclusively from\ndepth. Our approach builds on robust human keypoint detectors for color images\nand incorporates depth for lifting into 3D. We combine the system with our\nlearning from demonstration framework to instruct a service robot without the\nneed of markers. Experiments in real world settings demonstrate that our\napproach enables a PR2 robot to imitate manipulation actions observed from a\nhuman teacher.","url_abs":"http://arxiv.org/abs/1803.02622v2","url_pdf":"http://arxiv.org/pdf/1803.02622v2.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":"3d-human-pose-estimation-in-rgbd-images-for","repo_url":"https://github.com/lmb-freiburg/rgbd-pose3d","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"3d-human-pose-estimation","task_name":"3D Human Pose Estimation"},{"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-human-pose-estimation-on-total-capture","task":"3D Human Pose Estimation","dataset":"Total Capture","model":"ROS node wrapping","rank_in_archive_order":14,"of":14,"metrics":{"Average MPJPE (mm)":"112"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1803.02622","atlas_url":"https://app.syntology.ai/?focus=1803.02622","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}