مؤتمر
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
| العنوان: | DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations |
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| المؤلفون: | Van Zandycke, Gabriel, Somers, Vladimir, Istasse, Maxime, Del Don, Carlo, Zambrano, Davide, ACM MMSports 2022, 5th International ACM Workshop on Multimedia Content Analysis in Sports |
| المساهمون: | Sportradar, UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique |
| المصدر: | MMSports '22: Proceedings of the 5th International ACM Workshop on Multimedia Content Analysis in Sports, Vol. Octobre 2022, no.1, p. 1-8 (2022) |
| بيانات النشر: | Association for Computing Machinery |
| سنة النشر: | 2022 |
| المجموعة: | DIAL@UCL (Université catholique de Louvain) |
| مصطلحات موضوعية: | challenge, competition, dataset, deep learning, computer vision, image understanding, sports, basketball, ball 3D localization, camera calibration, instance segmentation, person re-identification, reid, court registration |
| الوصف: | With the recent development of Deep Learning applied to Computer Vision, sport video understanding has gained a lot of attention, providing much richer information for both sport consumers and leagues. This paper introduces DeepSportradar-v1, a suite of computer vision tasks, datasets and benchmarks for automated sport understanding. The main purpose of this framework is to close the gap between academic research and real world settings. To this end, the datasets provide high-resolution raw images, camera parameters and high quality annotations. 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. To encourage further research on advanced methods for sport understanding, a competition is organized as part of the MMSports workshop from the ACM Multimedia 2022 conference, where participants have to develop state-of-the-art methods to solve the above tasks. The four datasets, development kits and baselines are publicly available at https://github.com/DeepSportRadarTest. |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| العلاقة: | boreal:269451; http://hdl.handle.net/2078.1/269451Test |
| DOI: | 10.1145/3552437.3555699 |
| الإتاحة: | https://doi.org/10.1145/3552437.3555699Test http://hdl.handle.net/2078.1/269451Test |
| حقوق: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.34413226 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1145/3552437.3555699 |
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