{"url":"/dataset/once","name":"ONCE","full_name":"One Million Scenes","description_markdown":"ONCE (One millioN sCenEs) is a dataset for 3D object detection in the autonomous driving scenario. The ONCE dataset consists of 1 million LiDAR scenes and 7 million corresponding camera images. The data is selected from 144 driving hours, which is 20x longer than other 3D autonomous driving datasets available like [nuScenes](nuscenes) and [Waymo](waymo-open-dataset), and it is collected across a range of different areas, periods and weather conditions. \r\n\r\nConsists of:\r\n\r\n* 1 Million LiDAR frames, 7 Million camera images\r\n\r\n* 200 km² driving regions, 144 driving hours\r\n\r\n* 15k fully annotated scenes with 5 classes (Car, Bus, Truck, Pedestrian, Cyclist)\r\n\r\n* Diverse environments (day/night, sunny/rainy, urban/suburban areas)","description_withheld":null,"homepage":"https://once-for-auto-driving.github.io/index.html","introduced_date":"2021-06-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/one-million-scenes-for-autonomous-driving","title":"One Million Scenes for Autonomous Driving: ONCE Dataset","first_author":"Jiageng Mao","url":null},"license":{"name":"CC BY-NC-SA 4.0","url":"https://once-for-auto-driving.github.io/licenses.html"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"LiDAR","url":"/datasets/modality/lidar"}],"tasks":[{"name":"3D Object Detection","url":"/task/3d-object-detection","datasets_with_task":"/datasets/task/3d-object-detection"}],"languages":[],"variants":["ONCE"],"data_loaders":[],"num_papers_in_archive":87,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-object-detection-on-once","task":"3D Object Detection","dataset_variant":"ONCE","rows":2,"metrics":[" mAP"],"first_row_in_archive_order":{"model":"LION","paper":"/paper/lion-linear-group-rnn-for-3d-object-detection","metrics":{" mAP":"66.6"},"code_links":[{"title":"happinesslz/LION","url":"https://github.com/happinesslz/LION"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/lion-linear-group-rnn-for-3d-object-detection","title":"LION: Linear Group RNN for 3D Object Detection in Point Clouds","date":"2024-07-25","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":0,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/center-based-3d-object-detection-and-tracking","title":"Center-based 3D Object Detection and Tracking","date":"2020-06-19","rows_on_this_dataset":1,"code_links":13,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":22,"samples_ran":7,"samples_unverified":15,"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":29,"samples_ran":7,"samples_unverified":22,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":1,"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."}