{"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/labelmaker-automatic-semantic-label","title":"LABELMAKER: Automatic Semantic Label Generation from RGB-D Trajectories","arxiv_id":"2311.12174","date":"2023-11-20","proceeding":null,"authors":["Silvan Weder","Hermann Blum","Francis Engelmann","Marc Pollefeys"],"abstract":"Semantic annotations are indispensable to train or evaluate perception models, yet very costly to acquire. This work introduces a fully automated 2D/3D labeling framework that, without any human intervention, can generate labels for RGB-D scans at equal (or better) level of accuracy than comparable manually annotated datasets such as ScanNet. Our approach is based on an ensemble of state-of-the-art segmentation models and 3D lifting through neural rendering. We demonstrate the effectiveness of our LabelMaker pipeline by generating significantly better labels for the ScanNet datasets and automatically labelling the previously unlabeled ARKitScenes dataset. Code and models are available at https://labelmaker.org","url_abs":"https://arxiv.org/abs/2311.12174v1","url_pdf":"https://arxiv.org/pdf/2311.12174v1.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":"labelmaker-automatic-semantic-label","repo_url":"https://github.com/cvg/labelmaker","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"neural-rendering","task_name":"Neural Rendering"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/semantic-segmentation-on-replica","task":"Semantic Segmentation","dataset":"Replica","model":"LabelMaker","rank_in_archive_order":1,"of":5,"metrics":{"mIoU":"42.1"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2311.12174","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.12174"}},"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/cvg/labelmaker","reach":null}],"summary":{"ran_honours":2,"ran_fixture":1},"by_repo_kind":{"official":{"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":"d8dd12cd87ad99c3","entry":"get_closest_timestamp","repo":"cvg/labelmaker","repo_kind":"official","path":"scripts/arkitscenes2labelmaker.py","file_url":"https://github.com/cvg/labelmaker/blob/HEAD/scripts/arkitscenes2labelmaker.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"d8dd12cd87ad99c3"}},{"code_sha256_prefix":"7bb7defc55e0974c","entry":"load_intrinsics","repo":"cvg/labelmaker","repo_kind":"official","path":"scripts/arkitscenes2labelmaker.py","file_url":"https://github.com/cvg/labelmaker/blob/HEAD/scripts/arkitscenes2labelmaker.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":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"7bb7defc55e0974c"}},{"code_sha256_prefix":"d7003e7862154cbd","entry":"project_pointcloud","repo":"cvg/labelmaker","repo_kind":"official","path":"labelmaker/lifting_3d/lifting_points.py","file_url":"https://github.com/cvg/labelmaker/blob/HEAD/labelmaker/lifting_3d/lifting_points.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"d7003e7862154cbd"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}