{"url":"/dataset/deepsportradar-v1","name":"DeepSportRadar-v1","full_name":null,"description_markdown":"**DeepSportradar** is a benchmark suite of computer vision tasks, datasets and benchmarks for automated sport understanding. DeepSportradar currently supports four challenging tasks related to basketball: ball 3D localization, camera calibration, player instance segmentation and player re-identification. For each of the four tasks, a detailed description of the dataset, objective, performance metrics, and the proposed baseline method are provided. \r\n\r\nSource: [DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations](https://arxiv.org/pdf/2208.08190v1.pdf)\r\n\r\nImage Source: [https://github.com/deepsportradar/instance-segmentation-challenge](https://github.com/deepsportradar/instance-segmentation-challenge)","description_withheld":null,"homepage":"https://github.com/DeepSportRadar","introduced_date":"2022-08-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/deepsportradar-v1-computer-vision-dataset-for","title":"DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations","first_author":"Gabriel Van Zandycke","url":null},"license":{"name":"Apache-2.0 license","url":"https://github.com/DeepSportRadar/instance-segmentation-challenge/blob/master/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Instance Segmentation","url":"/task/instance-segmentation","datasets_with_task":"/datasets/task/instance-segmentation"},{"name":"Video Understanding","url":"/task/video-understanding","datasets_with_task":"/datasets/task/video-understanding"},{"name":"Camera Calibration","url":"/task/camera-calibration","datasets_with_task":"/datasets/task/camera-calibration"},{"name":"Sports Understanding","url":"/task/sports-understanding","datasets_with_task":"/datasets/task/sports-understanding"}],"languages":[],"variants":["DeepSportRadar-v1"],"data_loaders":[],"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."}