{"url":"/dataset/viso","name":"VISO","full_name":"VIdeo Satellite Objects","description_markdown":"This dataset is a large-scale dataset for moving object detection and tracking in satellite videos, which consists of 40 satellite videos captured by Jilin-1 satellite platforms. Each image has a resolution of 12000x5000 and contains a great number of objects with different scales. Four common types of vechicles, including plane, car, ship, and train, are manually-labeled. A total of 853,911 instances are labeled by axis-aligned bounding boxes.\r\nhttps://paperswithcode.com/paper/detecting-and-tracking-small-and-dense-moving","description_withheld":null,"homepage":"https://github.com/qingyonghu/viso","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["VISO"],"data_loaders":[],"num_papers_in_archive":1,"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."}