{"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-from-depth-maps","title":"3D human pose estimation from depth maps using a deep combination of poses","arxiv_id":"1807.05389","date":"2018-07-14","proceeding":null,"authors":["Manuel J. Marin-Jimenez","Francisco J. Romero-Ramirez","Rafael Muñoz-Salinas","Rafael Medina-Carnicer"],"abstract":"Many real-world applications require the estimation of human body joints for\nhigher-level tasks as, for example, human behaviour understanding. In recent\nyears, depth sensors have become a popular approach to obtain three-dimensional\ninformation. The depth maps generated by these sensors provide information that\ncan be employed to disambiguate the poses observed in two-dimensional images.\nThis work addresses the problem of 3D human pose estimation from depth maps\nemploying a Deep Learning approach. We propose a model, named Deep Depth Pose\n(DDP), which receives a depth map containing a person and a set of predefined\n3D prototype poses and returns the 3D position of the body joints of the\nperson. In particular, DDP is defined as a ConvNet that computes the specific\nweights needed to linearly combine the prototypes for the given input. We have\nthoroughly evaluated DDP on the challenging 'ITOP' and 'UBC3V' datasets, which\nrespectively depict realistic and synthetic samples, defining a new\nstate-of-the-art on them.","url_abs":"http://arxiv.org/abs/1807.05389v1","url_pdf":"http://arxiv.org/pdf/1807.05389v1.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-from-depth-maps","repo_url":"https://github.com/AVAuco/ddp","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"3d-human-pose-estimation","task_name":"3D Human Pose Estimation"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}