{"url":"/dataset/dynamicmap","name":"semi-indoor","full_name":null,"description_markdown":"collected by one VLP-16 in a small vehicle (1m x 1m)","description_withheld":null,"homepage":"https://github.com/KTH-RPL/DynamicMap_Benchmark","introduced_date":"2023-05-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-dynamic-points-removal-benchmark-in-point","title":"A Dynamic Points Removal Benchmark in Point Cloud Maps","first_author":"Qingwen Zhang","url":null},"license":null,"modalities":[],"tasks":[{"name":"Dynamic Point Removal","url":"/task/dynamic-point-removal","datasets_with_task":"/datasets/task/dynamic-point-removal"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["semi-indoor"],"data_loaders":[{"repo":"https://github.com/kth-rpl/dynamicmap_benchmark","url":"https://github.com/kth-rpl/dynamicmap_benchmark","frameworks":[]}],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/dynamic-point-removal-on-semi-indoor","task":"Dynamic Point Removal","dataset_variant":"semi-indoor","rows":4,"metrics":["associated accuracy"],"first_row_in_archive_order":{"model":"Octomap","paper":null,"metrics":{"associated accuracy":"85.51"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"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."}