{"url":"/dataset/hd1k","name":"HD1k","full_name":null,"description_markdown":"An autnonomous driving dataset and benchmark for optical flow. This dataset was created by the Heidelberg Collaboratory for Image Processing in close cooperation with Robert Bosch GmbH.\r\n\r\nFor the public training dataset, we provide:\r\n\r\n1) > 1000 frames at 2560x1080 with diverse lighting and weather scenarios\r\n\r\n2) reference data with error bars for optical flow\r\n\r\n3) evaluation masks for dynamic objects\r\n\r\n4) specific robustness evaluation on challenging scenes\r\n\r\nThe data was captured in a controlled environment with systematic variation of traffic scenarios, weather, and lighting conditions. The data was acquired at a frame rate of 200Hz with a resolution of 2560x1080.","description_withheld":null,"homepage":"http://hci-benchmark.iwr.uni-heidelberg.de/","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Optical Flow Estimation","url":"/task/optical-flow-estimation","datasets_with_task":"/datasets/task/optical-flow-estimation"}],"languages":[],"variants":["HD1k"],"data_loaders":[{"repo":"https://github.com/pytorch/vision","url":"https://pytorch.org/vision/stable/generated/torchvision.datasets.HD1K.html","frameworks":["pytorch"]}],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}