{"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/reconstructing-animatable-categories-from","title":"Reconstructing Animatable Categories from Videos","arxiv_id":"2305.06351","date":"2023-05-10","proceeding":"CVPR 2023 1","authors":["Gengshan Yang","Chaoyang Wang","N Dinesh Reddy","Deva Ramanan"],"abstract":"Building animatable 3D models is challenging due to the need for 3D scans, laborious registration, and manual rigging, which are difficult to scale to arbitrary categories. Recently, differentiable rendering provides a pathway to obtain high-quality 3D models from monocular videos, but these are limited to rigid categories or single instances. We present RAC that builds category 3D models from monocular videos while disentangling variations over instances and motion over time. Three key ideas are introduced to solve this problem: (1) specializing a skeleton to instances via optimization, (2) a method for latent space regularization that encourages shared structure across a category while maintaining instance details, and (3) using 3D background models to disentangle objects from the background. We show that 3D models of humans, cats, and dogs can be learned from 50-100 internet videos.","url_abs":"https://arxiv.org/abs/2305.06351v1","url_pdf":"https://arxiv.org/pdf/2305.06351v1.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":"reconstructing-animatable-categories-from","repo_url":"https://github.com/gengshan-y/rac","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"reconstructing-animatable-categories-from","repo_url":"https://github.com/lab4d-org/lab4d","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"3d-shape-reconstruction-from-videos","task_name":"3D Shape Reconstruction from Videos"},{"task_slug":"dynamic-reconstruction","task_name":"Dynamic Reconstruction"},{"task_slug":"monocular-reconstruction","task_name":"Monocular Reconstruction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2305.06351","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.06351"}},"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/lab4d-org/lab4d","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/gengshan-y/rac","reach":{"status":"ok"}}],"summary":{"ran_draft_wrong":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":0,"samples":[{"code_sha256_prefix":"cd10466b0c2ff0e3","entry":"render_batch","repo":"lab4d-org/lab4d","repo_kind":"official","path":"lab4d/render.py","file_url":"https://github.com/lab4d-org/lab4d/blob/HEAD/lab4d/render.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"cd10466b0c2ff0e3"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}