{"url":"/dataset/arkit-labelmaker","name":"ARKit LabelMaker","full_name":null,"description_markdown":"We complement ARKitScenes dataset with dense semantic annotations that are automatically generated at scale. This produces the first large-scale, real-world 3D dataset with dense semantic annotations. Training on this auto-generated data, we push forward the state-of-the-art performance on ScanNet and ScanNet200 with prevalent 3D semantic segmentation models.","description_withheld":null,"homepage":"https://labelmaker.org","introduced_date":"2024-10-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/arkit-labelmaker-a-new-scale-for-indoor-3d","title":"ARKit LabelMaker: A New Scale for Indoor 3D Scene Understanding","first_author":"Guangda Ji","url":null},"license":{"name":"BSD license family","url":"https://github.com/cvg/LabelMaker/?tab=BSD-3-Clause-1-ov-file#readme"},"modalities":[],"tasks":[{"name":"3D Semantic Segmentation","url":"/task/3d-semantic-segmentation","datasets_with_task":"/datasets/task/3d-semantic-segmentation"}],"languages":[],"variants":["ARKit LabelMaker"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}