{"url":"/dataset/npo","name":"NPO","full_name":"Negative and Positive Obstacles","description_markdown":"The dataset is recorded with an on-vehicle ZED stereo camera in both urban and rural environments\r\n\r\nThe 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\r\nsnowy.\r\n\r\nNegative obstacles (i.e., potholes and cracks) and positive obstacles (i.e., pedestrians, cars, and motorcycles) in 5, 000 images are labelled","description_withheld":null,"homepage":"https://github.com/lab-sun/InconSeg","introduced_date":"2023-05-22","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"RGB-D","url":"/datasets/modality/rgb-d"}],"tasks":[{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"},{"name":"Segmentation","url":"/task/segmentation","datasets_with_task":"/datasets/task/segmentation"},{"name":"Road Damage Detection","url":"/task/road-damage-detection","datasets_with_task":"/datasets/task/road-damage-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"},{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["NPO"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/road-damage-detection-on-npo","task":"Road Damage Detection","dataset_variant":"NPO","rows":1,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"InconSeg","paper":"/paper/inconseg-residual-guided-fusion-with","metrics":{"mIoU":"83.88"},"code_links":[{"title":"lab-sun/inconseg","url":"https://github.com/lab-sun/inconseg"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/inconseg-residual-guided-fusion-with","title":"InconSeg: Residual-Guided Fusion With Inconsistent Multi-Modal Data for Negative and Positive Road Obstacles Segmentation","date":"2023-05-02","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+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."}