{"url":"/dataset/opentrench3d","name":"OpenTrench3D","full_name":null,"description_markdown":"OpenTrench3D, the first publicly available point cloud dataset of underground utilities from open trenches. It features 310 fully annotated point clouds consisting of a total of 528 million points categorised into 5 unique classes. OpenTrench3D consists of photogrammetrically derived 3D point clouds capturing detailed scenes of open trenches, revealing underground utilities.","description_withheld":null,"homepage":"https://github.com/SimonBuusJensen/OpenTrench3D","introduced_date":"2024-04-12","introduced_date_note":null,"introduced_by":null,"license":{"name":"CC BY-NC 4.0","url":"https://creativecommons.org/licenses/by-nc/4.0/"},"modalities":[{"name":"3D","url":"/datasets/modality/3d"},{"name":"Point cloud","url":"/datasets/modality/point-cloud"}],"tasks":[{"name":"3D Semantic Segmentation","url":"/task/3d-semantic-segmentation","datasets_with_task":"/datasets/task/3d-semantic-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["OpenTrench3D"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-semantic-segmentation-on-opentrench3d","task":"3D Semantic Segmentation","dataset_variant":"OpenTrench3D","rows":3,"metrics":["mIoU","mAcc","Model Size"],"first_row_in_archive_order":{"model":"PointVector-XL","paper":"/paper/point-is-a-vector-a-feature-representation-in","metrics":{"Model Size":"24.1M","mAcc":"84.1","mIoU":"76.5"},"code_links":[{"title":"guochengqian/openpoints","url":"https://github.com/guochengqian/openpoints/blob/master/models/backbone/pointvector.py"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/meta-architecure-for-point-cloud-analysis","title":"Meta Architecture for Point Cloud Analysis","date":"2022-11-26","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/pointnext-revisiting-pointnet-with-improved","title":"PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies","date":"2022-06-09","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":17,"samples_ran":7,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/point-is-a-vector-a-feature-representation-in","title":"PointVector: A Vector Representation In Point Cloud Analysis","date":"2022-05-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":1,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":28,"samples_ran":8,"samples_unverified":20,"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."}