Feb. 6, 2024, 5:45 a.m. | Emil HovadAlexandra Instituttet A/S, Rued Langgaards Vej 7, 2300 K{\o}benhavn S, Denmark, Department of Mathematics and Computer Science, Technical Un

cs.LG updates on arXiv.org arxiv.org

Recent advances of deep learning makes it possible to identify specific events in videos with greater precision. This has great relevance in sports like tennis in order to e.g., automatically collect game statistics, or replay actions of specific interest for game strategy or player improvements. In this paper, we investigate the potential and the challenges of using deep learning to classify tennis actions. Three models of different size, all based on the deep learning architecture SlowFast were trained and evaluated …

advances classification cs.cv cs.lg deep learning events game identify improvements paper precision sports statistics strategy tennis videos

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