{"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/modeling-3d-shapes-by-reinforcement-learning","title":"Modeling 3D Shapes by Reinforcement Learning","arxiv_id":"2003.12397","date":"2020-03-27","proceeding":"ECCV 2020 8","authors":["Cheng Lin","Tingxiang Fan","Wenping Wang","Matthias Nießner"],"abstract":"We explore how to enable machines to model 3D shapes like human modelers using deep reinforcement learning (RL). In 3D modeling software like Maya, a modeler usually creates a mesh model in two steps: (1) approximating the shape using a set of primitives; (2) editing the meshes of the primitives to create detailed geometry. Inspired by such artist-based modeling, we propose a two-step neural framework based on RL to learn 3D modeling policies. By taking actions and collecting rewards in an interactive environment, the agents first learn to parse a target shape into primitives and then to edit the geometry. To effectively train the modeling agents, we introduce a novel training algorithm that combines heuristic policy, imitation learning and reinforcement learning. Our experiments show that the agents can learn good policies to produce regular and structure-aware mesh models, which demonstrates the feasibility and effectiveness of the proposed RL framework.","url_abs":"https://arxiv.org/abs/2003.12397v3","url_pdf":"https://arxiv.org/pdf/2003.12397v3.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":"modeling-3d-shapes-by-reinforcement-learning","repo_url":"https://github.com/IMAC-projects/mesh-deformation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"modeling-3d-shapes-by-reinforcement-learning","repo_url":"https://github.com/clinplayer/3DModelingRL","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"deep-reinforcement-learning","task_name":"Deep Reinforcement Learning"},{"task_slug":"imitation-learning","task_name":"Imitation Learning"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2003.12397","atlas_url":"https://app.syntology.ai/?focus=2003.12397","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.12397"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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/clinplayer/3DModelingRL","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/IMAC-projects/mesh-deformation","reach":{"status":"ok"}}],"summary":{"ran_draft_wrong":3},"by_repo_kind":{"listed":{"samples":3,"ran":3,"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":"7dc0ccf56d156abb","entry":"read_as_3d_array","repo":"clinplayer/3DModelingRL","repo_kind":"listed","path":"Mesh-Agent/utils/binvox_rw.py","file_url":"https://github.com/clinplayer/3DModelingRL/blob/HEAD/Mesh-Agent/utils/binvox_rw.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"7dc0ccf56d156abb"}},{"code_sha256_prefix":"d3b3bb299e8acb92","entry":"read_as_coord_array","repo":"clinplayer/3DModelingRL","repo_kind":"listed","path":"Mesh-Agent/utils/binvox_rw.py","file_url":"https://github.com/clinplayer/3DModelingRL/blob/HEAD/Mesh-Agent/utils/binvox_rw.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d3b3bb299e8acb92"}},{"code_sha256_prefix":"ba966c4838f2c939","entry":"read_header","repo":"clinplayer/3DModelingRL","repo_kind":"listed","path":"Mesh-Agent/utils/binvox_rw.py","file_url":"https://github.com/clinplayer/3DModelingRL/blob/HEAD/Mesh-Agent/utils/binvox_rw.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"ba966c4838f2c939"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}