Datasets › NPO

NPO (Negative and Positive Obstacles)

22 May 2023 archive 2025-07-28

The dataset is recorded with an on-vehicle ZED stereo camera in both urban and rural environments

The dataset contains various lighting conditions, such as normal lights, large-area shadows, dim lights, and sun glare. There are also different weather conditions, such as sunny, cloudy, and snowy.

Negative obstacles (i.e., potholes and cracks) and positive obstacles (i.e., pedestrians, cars, and motorcycles) in 5, 000 images are labelled

Benchmarks archive 2025-07-28

All 1 leaderboard 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.

First row (archive order)PaperCode
Road Damage Detection NPO InconSeg mIoU 83.88 InconSeg: Residual-Guided Fusion With Inconsistent... lab-sun/inconseg 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper 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 1. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • NPO

1 variant name, as the archive lists them.

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