{"url":"/dataset/drone-vs-bird","name":"Drone vs Bird","full_name":"Drone vs Bird Detection Challenge","description_markdown":"For the Drone-vs-Bird Detection Challenge 2021, 77 different video sequences have been made available as training data. These video sequences originate from the previous installment of the challenge and were collected using MPEG4-coded static cameras by the SafeShore project, by the Fraunhofer IOSB research institute and by the ALADDIN2 project. On average, the video sequences consist of 1,384 frames, while each frame contains 1.12 annotated drones. The video sequences are recorded with both static cameras and moving cameras and the resolution varies between 720×576 and 3840×2160 pixels. In total, 8 different types of drones exist in the dataset , i.e. 3 with fixed wings and 5 rotary ones. For each video, a separate annotation file is provided, which contains the frame number and the bounding box (expressed as [topx topy width height]) for the frames in which drones enter the scenes.\r\n\r\nSource: [Drone-vs-Bird Detection Challenge at IEEE AVSS2021\r\n](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9663844&casa_token=yyGQLesXf_QAAAAA:sKtn96xAwk_63tadtkOjNIivpIwXZ-fXJ1if8zzXcy4ZbEwfwq-8udMsldorBUfmr0xO9e9Ubg&tag=1)","description_withheld":null,"homepage":"https://wosdetc2021.wordpress.com/drone-vs-bird-detection-challenge/","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"}],"languages":[],"variants":["Drone vs Bird"],"data_loaders":[{"repo":"https://github.com/mili4302/BirdDroneDataset","url":"https://github.com/mili4302/BirdDroneDataset.git","frameworks":["pytorch"]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-detection-on-drone-vs-bird","task":"Object Detection","dataset_variant":"Drone vs Bird","rows":2,"metrics":["AP50","AP50l","AP50m","AP50s"],"first_row_in_archive_order":{"model":"OBSS YOLOv5+Track Boosting (Including Synthetic Data)","paper":"/paper/track-boosting-and-synthetic-data-aided-drone","metrics":{"AP50":"79.4","AP50l":"70.3","AP50m":"72.7","AP50s":"86.2"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/track-boosting-and-synthetic-data-aided-drone","title":"Track Boosting and Synthetic Data Aided Drone Detection","date":"2021-11-24","rows_on_this_dataset":2,"code_links":0,"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."}