Datasets › LaRS

LaRS (Lakes, Rivers and Seas Dataset)

Introduced by Lojze Žust et al. in LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark18 Aug 2023 archive 2025-07-28

LaRS is the largest and most diverse panoptic maritime obstacle detection dataset.

Highlights:

  • Diverse scenes from manual capture, public online videos and existing datasets
  • USV-centric point of view
  • 4000+ manually per-pixel labelled frames:
    • 3 stuff categories and 8 thing (dynamic obstacles) categories
    • 20 scene-level attributes (e.g. illumination, reflections, conditions)
  • Temporal context for each annotated frame (9 preceding frames, total: 40k frames)

Benchmarks archive 2025-07-28

All 3 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

Papers archive 2025-07-28

2 shown of 2 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 5. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 0 4 23 Nov 2023 not harvested
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark 2 27 18 Aug 2023 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC-BY-NC 4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • LaRS

1 variant name, as the archive lists them.

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