{"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/video-based-reconstruction-of-3d-people","title":"Video Based Reconstruction of 3D People Models","arxiv_id":"1803.04758","date":"2018-03-13","proceeding":"CVPR 2018 6","authors":["Thiemo Alldieck","Marcus Magnor","Weipeng Xu","Christian Theobalt","Gerard Pons-Moll"],"abstract":"This paper describes how to obtain accurate 3D body models and texture of\narbitrary people from a single, monocular video in which a person is moving.\nBased on a parametric body model, we present a robust processing pipeline\nachieving 3D model fits with 5mm accuracy also for clothed people. Our main\ncontribution is a method to nonrigidly deform the silhouette cones\ncorresponding to the dynamic human silhouettes, resulting in a visual hull in a\ncommon reference frame that enables surface reconstruction. This enables\nefficient estimation of a consensus 3D shape, texture and implanted animation\nskeleton based on a large number of frames. We present evaluation results for a\nnumber of test subjects and analyze overall performance. Requiring only a\nsmartphone or webcam, our method enables everyone to create their own fully\nanimatable digital double, e.g., for social VR applications or virtual try-on\nfor online fashion shopping.","url_abs":"http://arxiv.org/abs/1803.04758v3","url_pdf":"http://arxiv.org/pdf/1803.04758v3.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":"video-based-reconstruction-of-3d-people","repo_url":"https://github.com/thmoa/videoavatars","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"3d-reconstruction","task_name":"3D Reconstruction"},{"task_slug":"surface-reconstruction","task_name":"Surface Reconstruction"},{"task_slug":"virtual-try-on","task_name":"Virtual Try-on"}],"methods":[],"datasets_introduced":[{"slug":"people-snapshot-dataset","name":"People Snapshot Dataset","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.04758","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.04758"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/thmoa/videoavatars","reach":null}],"summary":{"ran_honours":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"a2fe4c3c9bea6fc4","entry":"pose_prior_obj","repo":"thmoa/videoavatars","repo_kind":"official","path":"step1_pose.py","file_url":"https://github.com/thmoa/videoavatars/blob/HEAD/step1_pose.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"a2fe4c3c9bea6fc4"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}