{"url":"/dataset/lars","name":"LaRS","full_name":"Lakes, Rivers and Seas Dataset","description_markdown":"LaRS is the largest and most diverse **panoptic** maritime obstacle detection dataset.\r\n\r\nHighlights:\r\n\r\n* Diverse scenes from manual capture, public online videos and existing datasets  \r\n* USV-centric point of view  \r\n* **4000+** manually per-pixel labelled frames:  \r\n    * **3 stuff** categories and **8 thing** (dynamic obstacles) categories  \r\n    * 20 scene-level attributes (e.g. illumination, reflections, conditions)  \r\n* **Temporal context** for each annotated frame (9 preceding frames, total: 40k frames)","description_withheld":null,"homepage":"https://lojzezust.github.io/lars-dataset/","introduced_date":"2023-08-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/lars-a-diverse-panoptic-maritime-obstacle","title":"LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark","first_author":"Lojze Žust","url":null},"license":{"name":"CC-BY-NC 4.0","url":"https://lojzezust.github.io/lars-dataset/terms.html"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Panoptic Segmentation","url":"/task/panoptic-segmentation","datasets_with_task":"/datasets/task/panoptic-segmentation"},{"name":"Video Semantic Segmentation","url":"/task/video-semantic-segmentation","datasets_with_task":"/datasets/task/video-semantic-segmentation"},{"name":"Video Panoptic Segmentation","url":"/task/video-panoptic-segmentation","datasets_with_task":"/datasets/task/video-panoptic-segmentation"}],"languages":[],"variants":["LaRS"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semantic-segmentation-on-lars","task":"Semantic Segmentation","dataset_variant":"LaRS","rows":20,"metrics":["Q","F1","μ","mIoU"],"first_row_in_archive_order":{"model":"SWIM^2 (Mask2Former)","paper":"/paper/the-2nd-workshop-on-maritime-computer-vision","metrics":{"F1":"79.9","Q":"78.1","mIoU":"97.8","μ":"79.7 "},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/panoptic-segmentation-on-lars","task":"Panoptic Segmentation","dataset_variant":"LaRS","rows":8,"metrics":["PQ"],"first_row_in_archive_order":{"model":"Mask2Former (Swin-B)","paper":"/paper/lars-a-diverse-panoptic-maritime-obstacle","metrics":{"PQ":"41.7"},"code_links":[{"title":"lojzezust/lars_evaluator","url":"https://github.com/lojzezust/lars_evaluator"},{"title":"lojzezust/mmsegmentation-macvi","url":"https://github.com/lojzezust/mmsegmentation-macvi"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/video-semantic-segmentation-on-lars","task":"Video Semantic Segmentation","dataset_variant":"LaRS","rows":3,"metrics":["Q","F1","μ","mIoU"],"first_row_in_archive_order":{"model":"WaSR-T (ResNet-101)","paper":"/paper/lars-a-diverse-panoptic-maritime-obstacle","metrics":{"F1":"62.1","Q":"60.1","mIoU":"96.7","μ":"71.1"},"code_links":[{"title":"lojzezust/lars_evaluator","url":"https://github.com/lojzezust/lars_evaluator"},{"title":"lojzezust/mmsegmentation-macvi","url":"https://github.com/lojzezust/mmsegmentation-macvi"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/the-2nd-workshop-on-maritime-computer-vision","title":"The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024","date":"2023-11-23","rows_on_this_dataset":4,"code_links":0,"syntology":null},{"paper":"/paper/lars-a-diverse-panoptic-maritime-obstacle","title":"LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark","date":"2023-08-18","rows_on_this_dataset":27,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+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."}