{"url":"/dataset/llamas","name":"LLAMAS","full_name":"Labeled Lane Markers","description_markdown":"The unsupervised Labeled Lane MArkerS dataset (LLAMAS) is a dataset for lane detection and segmentation. It contains over 100,000 annotated images, with annotations of over 100 meters at a resolution of 1276 x 717 pixels. The Unsupervised Llamas dataset was annotated by creating high definition maps for automated driving including lane markers based on Lidar. \r\n\r\nPaper: [Unsupervised Labeled Lane Markers Using Maps](https://doi.org/10.1109/ICCVW.2019.00111)\r\n\r\nSource: [Unsupervised Llamas Lane Marker Dataset](https://unsupervised-llamas.com/llamas/)\r\n\r\nImage Source: [Unsupervised Llamas Lane Marker Dataset](https://unsupervised-llamas.com/llamas/)","description_withheld":null,"homepage":"https://unsupervised-llamas.com/llamas/","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Lane Detection","url":"/task/lane-detection","datasets_with_task":"/datasets/task/lane-detection"}],"languages":[],"variants":["LLAMAS"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/lane-detection-on-llamas","task":"Lane Detection","dataset_variant":"LLAMAS","rows":10,"metrics":["F1","mF1"],"first_row_in_archive_order":{"model":"CLRNet (DLA-34)","paper":"/paper/clrnet-cross-layer-refinement-network-for","metrics":{"F1":"0.9612"},"code_links":[{"title":"Turoad/lanedet","url":"https://github.com/Turoad/lanedet"},{"title":"Turoad/clrnet","url":"https://github.com/Turoad/clrnet"},{"title":"zkyseu/PPlanedet","url":"https://github.com/zkyseu/PPlanedet"},{"title":"zkyntu/UnLanedet","url":"https://github.com/zkyntu/UnLanedet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/fenet-focusing-enhanced-network-for-lane","title":"FENet: Focusing Enhanced Network for Lane Detection","date":"2023-12-28","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/clrnet-cross-layer-refinement-network-for","title":"CLRNet: Cross Layer Refinement Network for Lane Detection","date":"2022-03-19","rows_on_this_dataset":2,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":0,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/rethinking-efficient-lane-detection-via-curve","title":"Rethinking Efficient Lane Detection via Curve Modeling","date":"2022-03-04","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":0,"samples_unverified":12,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/laneaf-robust-multi-lane-detection-with","title":"LaneAF: Robust Multi-Lane Detection with Affinity Fields","date":"2021-03-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/keep-your-eyes-on-the-lane-attention-guided","title":"Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection","date":"2020-10-22","rows_on_this_dataset":3,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":1,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/polylanenet-lane-estimation-via-deep","title":"PolyLaneNet: Lane Estimation via Deep Polynomial Regression","date":"2020-04-23","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":0,"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":4,"samples_harvested":30,"samples_ran":1,"samples_unverified":29,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":3,"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."}