{"url":"/dataset/openlane","name":"OpenLane","full_name":null,"description_markdown":"**OpenLane** is the first real-world and the largest scaled 3D lane dataset to date. The dataset collects valuable contents from public perception dataset [Waymo Open Dataset](/dataset/waymo-open-dataset) and provides lane&closest-in-path object(CIPO) annotation for 1000 segments. In short, OpenLane owns 200K frames and over 880K carefully annotated lanes. The OpenLane Dataset is publicly released to aid the research community in making advancements in 3D perception and autonomous driving technology.","description_withheld":null,"homepage":"https://github.com/OpenDriveLab/OpenLane","introduced_date":"2022-03-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/persformer-3d-lane-detection-via-perspective-1","title":"PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark","first_author":"Li Chen","url":null},"license":{"name":"CC BY-NC-SA 4.0","url":"https://creativecommons.org/licenses/by-nc-sa/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Lane Detection","url":"/task/lane-detection","datasets_with_task":"/datasets/task/lane-detection"},{"name":"3D Lane Detection","url":"/task/3d-lane-detection","datasets_with_task":"/datasets/task/3d-lane-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["OpenLane"],"data_loaders":[{"repo":"https://github.com/OpenDriveLab/OpenLane","url":"https://github.com/OpenDriveLab/OpenLane","frameworks":["pytorch"]}],"num_papers_in_archive":46,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-lane-detection-on-openlane","task":"3D Lane Detection","dataset_variant":"OpenLane","rows":21,"metrics":["F1 (all)","Up & Down","Curve","Extreme Weather","Night","Intersection","Merge & Split","FPS (pytorch)"],"first_row_in_archive_order":{"model":"GLane3D(Swin-B)","paper":"/paper/glane3d-detecting-lanes-with-graph-of-3d","metrics":{"Curve":"72.7","Extreme Weather":"63.8","F1 (all)":"66.0","Intersection":"57.9","Merge & Split":"67.7","Night":"62.0","Up & Down":"61.7"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/lane-detection-on-openlane","task":"Lane Detection","dataset_variant":"OpenLane","rows":3,"metrics":["F1 score"],"first_row_in_archive_order":{"model":"CondLSTR (ResNet-18)","paper":"/paper/generating-dynamic-kernels-via-transformers","metrics":{"F1 score":"60.1"},"code_links":[{"title":"czyczyyzc/CondLSTR","url":"https://github.com/czyczyyzc/CondLSTR"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/glane3d-detecting-lanes-with-graph-of-3d","title":"GLane3D : Detecting Lanes with Graph of 3D Keypoints","date":"2025-03-31","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/repvf-a-unified-vector-fields-representation","title":"RepVF: A Unified Vector Fields Representation for Multi-task 3D Perception","date":"2024-07-15","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":4,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/lanecpp-continuous-3d-lane-detection-using-1","title":"LaneCPP: Continuous 3D Lane Detection using Physical Priors","date":"2024-06-12","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/pvalane-prior-guided-3d-lane-detection-with","title":"PVALane: Prior-Guided 3D Lane Detection with View-Agnostic Feature Alignment","date":"2024-03-24","rows_on_this_dataset":3,"code_links":0,"syntology":null},{"paper":"/paper/latr-3d-lane-detection-from-monocular-images","title":"LATR: 3D Lane Detection from Monocular Images with Transformer","date":"2023-08-08","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":11,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/anchor3dlane-learning-to-regress-3d-anchors","title":"Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane Detection","date":"2023-01-06","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/generating-dynamic-kernels-via-transformers","title":"Generating Dynamic Kernels via Transformers for Lane Detection","date":"2023-01-01","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/bev-lane-det-fast-lane-detection-on-bev","title":"BEV-LaneDet: a Simple and Effective 3D Lane Detection Baseline","date":"2022-10-12","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/curveformer-3d-lane-detection-by-curve","title":"CurveFormer: 3D Lane Detection by Curve Propagation with Curve Queries and Attention","date":"2022-09-16","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/m-2-3dlanenet-multi-modal-3d-lane-detection","title":"M$^2$-3DLaneNet: Exploring Multi-Modal 3D Lane Detection","date":"2022-09-13","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/petrv2-a-unified-framework-for-3d-perception","title":"PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images","date":"2022-06-02","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/persformer-3d-lane-detection-via-perspective-1","title":"PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark","date":"2022-03-21","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":15,"samples_ran":8,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/gen-lanenet-a-generalized-and-scalable","title":"Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection","date":"2020-03-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/3d-lanenet-end-to-end-3d-multiple-lane","title":"3D-LaneNet: End-to-End 3D Multiple Lane Detection","date":"2018-11-26","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":36,"samples_ran":24,"samples_unverified":12,"pointer_only_for_licence":1,"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."}