{"url":"/dataset/hyko2-vis","name":"HyKo2-VIS","full_name":null,"description_markdown":"We present datasets containing urban traffic and rural road scenes recorded using hyperspectral snap-shot sensors mounted on a moving car. The novel hyperspectral cameras used can capture whole spectral cubes at up to 15 Hz. This emerging new sensor modality enables hyperspectral scene analysis for autonomous driving tasks. Up to the best of the author’s knowledge no such dataset has been published so far. The datasets contain synchronized 3-D laser, spectrometer and hyperspectral data. Dense ground truth annotations are provided as semantic labels, material and traversability. The hyperspectral data ranges from visible to near infrared wavelengths. We explain our recoding platform and method, the associated data format along with a code library for easy data consumption. The datasets are publicly available for download.","description_withheld":null,"homepage":"https://wp.uni-koblenz.de/hyko/","introduced_date":"2017-10-22","introduced_date_note":null,"introduced_by":{"paper":"/paper/hyko-a-spectral-dataset-for-scene","title":"HyKo: A Spectral Dataset for Scene Understanding","first_author":"Christian Winkens","url":null},"license":{"name":"CC BY-NC-SA 3.0","url":"https://creativecommons.org/licenses/by-nc-sa/3.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"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":["HyKo2-VIS"],"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-hyko2","task":"Hyperspectral Semantic Segmentation","dataset_variant":"HyKo2-VIS","rows":3,"metrics":["Accuracy","Average Accuracy","Average Jaccard","Avg. F1"],"first_row_in_archive_order":{"model":"RU-Net","paper":"/paper/hs3-bench-a-benchmark-and-strong-baseline-for","metrics":{"Accuracy":"86.72","Average Accuracy":"68.79","Average Jaccard":"58.64","Avg. F1":"69.19"},"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":"2026-09-24T18:15:14+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."}