{"url":"/dataset/hsi-drive-v2-0","name":"HSI-Drive v2.0","full_name":null,"description_markdown":"HSI-Drive is the hyperspectral image (HSI) dataset created by the Digital Electronics Design Group (GDED) of the University of the Basque Country (UPV/EHU). This database is intended to contribute to the research into the use of hyperspectral imaging for the development of advanced driver assistance systems (ADAS) and autonomous driving systems (ADS). The dataset contains a diverse set of images recorded with a small-size 25-band VNIR snapshot camera mounted on a moving automobile. The recordings have been made in different seasons of the year, at different day times, under different weather conditions and on different types of roads. The dataset contains images and videos classified and tagged accordingly to provide rich and diverse data.","description_withheld":null,"homepage":"https://ipaccess.ehu.eus/HSI-Drive/","introduced_date":"2024-11-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/hsi-drive-v2-0-more-data-for-new-challenges","title":"HSI-Drive v2.0: More Data for New Challenges in Scene Understanding for Autonomous Driving","first_author":"Jon Gutiérrez-Zaballa","url":null},"license":{"name":"custom non-commercial research license","url":"https://ipaccess.ehu.eus/HSI-Drive/#signup"},"modalities":[{"name":"Hyperspectral images","url":"/datasets/modality/hyperspectral-images"}],"tasks":[{"name":"Hyperspectral Image Segmentation","url":"/task/hyperspectral-image-segmentation","datasets_with_task":"/datasets/task/hyperspectral-image-segmentation"},{"name":"Hyperspectral Image Classification","url":"/task/hyperspectral-image-classification","datasets_with_task":"/datasets/task/hyperspectral-image-classification"},{"name":"Hyperspectral Semantic Segmentation","url":"/task/hyperspectral-semantic-segmentation","datasets_with_task":"/datasets/task/hyperspectral-semantic-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["HSI-Drive v2.0"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/hyperspectral-semantic-segmentation-on-hsi","task":"Hyperspectral Semantic Segmentation","dataset_variant":"HSI-Drive v2.0","rows":3,"metrics":["Accuracy","Average Accuracy","Avg. F1","Jaccard (Mean)"],"first_row_in_archive_order":{"model":"RU-Net","paper":"/paper/hs3-bench-a-benchmark-and-strong-baseline-for","metrics":{"Accuracy":"96.08","Average Accuracy":"79.82","Avg. F1":"82.34","Jaccard (Mean)":"72.18"},"code_links":[{"title":"nickstheisen/hyperseg","url":"https://github.com/nickstheisen/hyperseg"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/hs3-bench-a-benchmark-and-strong-baseline-for","title":"HS3-Bench: A Benchmark and Strong Baseline for Hyperspectral Semantic Segmentation in Driving Scenarios","date":"2024-09-17","rows_on_this_dataset":3,"code_links":1,"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."}