{"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/learning-to-fuse-2d-and-3d-image-cues-for","title":"Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation","arxiv_id":"1611.05708","date":"2016-11-17","proceeding":"ICCV 2017 10","authors":["Bugra Tekin","Pablo Márquez-Neila","Mathieu Salzmann","Pascal Fua"],"abstract":"Most recent approaches to monocular 3D human pose estimation rely on Deep\nLearning. They typically involve regressing from an image to either 3D joint\ncoordinates directly or 2D joint locations from which 3D coordinates are\ninferred. Both approaches have their strengths and weaknesses and we therefore\npropose a novel architecture designed to deliver the best of both worlds by\nperforming both simultaneously and fusing the information along the way. At the\nheart of our framework is a trainable fusion scheme that learns how to fuse the\ninformation optimally instead of being hand-designed. This yields significant\nimprovements upon the state-of-the-art on standard 3D human pose estimation\nbenchmarks.","url_abs":"http://arxiv.org/abs/1611.05708v3","url_pdf":"http://arxiv.org/pdf/1611.05708v3.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":"learning-to-fuse-2d-and-3d-image-cues-for","repo_url":"https://github.com/romanus/code_tekinetal_iccv17","is_official":0,"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":"monocular-3d-human-pose-estimation","task_name":"Monocular 3D Human Pose Estimation"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1611.05708","atlas_url":"https://app.syntology.ai/?focus=1611.05708","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}