{"url":"/dataset/xview","name":"xView","full_name":null,"description_markdown":"xView is one of the largest publicly available datasets of overhead imagery. It contains images from complex scenes around the world, annotated using bounding boxes. It contains over 1M object instances from 60 different classes.\r\n\r\nSource: [xView dataset](http://xviewdataset.org/)","description_withheld":null,"homepage":"http://xviewdataset.org/","introduced_date":"2018-02-22","introduced_date_note":null,"introduced_by":{"paper":"/paper/xview-objects-in-context-in-overhead-imagery","title":"xView: Objects in Context in Overhead Imagery","first_author":"Darius Lam","url":null},"license":{"name":"Custom","url":"http://xviewdataset.org/terms.html"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Image Super-Resolution","url":"/task/image-super-resolution","datasets_with_task":"/datasets/task/image-super-resolution"},{"name":"Object Detection In Aerial Images","url":"/task/object-detection-in-aerial-images","datasets_with_task":"/datasets/task/object-detection-in-aerial-images"},{"name":"Disaster Response","url":"/task/disaster-response","datasets_with_task":"/datasets/task/disaster-response"},{"name":"Geophysics","url":"/task/geophysics","datasets_with_task":"/datasets/task/geophysics"}],"languages":[],"variants":["xView"],"data_loaders":[],"num_papers_in_archive":93,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-detection-in-aerial-images-on-xview","task":"Object Detection In Aerial Images","dataset_variant":"xView","rows":3,"metrics":["AP50"],"first_row_in_archive_order":{"model":"MAE+MTP(ViT-L+RVSA)","paper":"/paper/mtp-advancing-remote-sensing-foundation-model","metrics":{"AP50":"19.4"},"code_links":[{"title":"vitae-transformer/mtp","url":"https://github.com/vitae-transformer/mtp"},{"title":"cuzyoung/crossearth","url":"https://github.com/cuzyoung/crossearth"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/mtp-advancing-remote-sensing-foundation-model","title":"MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining","date":"2024-03-20","rows_on_this_dataset":3,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":4,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":5,"samples_ran":4,"samples_unverified":1,"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."}