{"url":"/dataset/dota-2-0","name":"DOTA 2.0","full_name":"Dataset of Object deTection in Aerial images","description_markdown":"—In the past decade, object detection has achieved significant progress in natural images but not in aerial images, due to the\r\nmassive variations in the scale and orientation of objects caused by the bird’s-eye view of aerial images. More importantly, the lack of\r\nlarge-scale benchmarks has become a major obstacle to the development of object detection in aerial images (ODAI). In this paper,\r\nwe present a large-scale Dataset of Object deTection in Aerial images (DOTA) and comprehensive baselines for ODAI. The proposed\r\nDOTA dataset contains 1,793,658 object instances of 18 categories of oriented-bounding-box annotations collected from 11,268 aerial\r\nimages. Based on this large-scale and well-annotated dataset, we build baselines covering 10 state-of-the-art algorithms with over 70\r\nconfigurations, where the speed and accuracy performances of each model have been evaluated. Furthermore, we provide a code\r\nlibrary for ODAI and build a website for evaluating different algorithms. Previous challenges run on DOTA have attracted more than 1300\r\nteams worldwide. We believe that the expanded large-scale DOTA dataset, the extensive baselines, the code library and the challenges\r\ncan facilitate the designs of robust algorithms and reproducible research on the problem of object detection in aerial images.","description_withheld":null,"homepage":"https://captain-whu.github.io/DOTA/dataset.html","introduced_date":"2021-02-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/object-detection-in-aerial-images-a-large","title":"Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges","first_author":"Jian Ding","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection In Aerial Images","url":"/task/object-detection-in-aerial-images","datasets_with_task":"/datasets/task/object-detection-in-aerial-images"},{"name":"Oriented Object Detection","url":"/task/oriented-object-detection","datasets_with_task":"/datasets/task/oriented-object-detection"}],"languages":[],"variants":["DOTA 2.0"],"data_loaders":[],"num_papers_in_archive":10,"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."}