A new figure skating dataset and benchmark, FSAnno and FSBench, evaluates and improves multimodal large language models on technical and artistic understanding of figure skating.
A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision
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abstract
Deep learning has the potential to revolutionize sports performance, with applications ranging from perception and comprehension to decision. This paper presents a comprehensive survey of deep learning in sports performance, focusing on three main aspects: algorithms, datasets and virtual environments, and challenges. Firstly, we discuss the hierarchical structure of deep learning algorithms in sports performance which includes perception, comprehension and decision while comparing their strengths and weaknesses. Secondly, we list widely used existing datasets in sports and highlight their characteristics and limitations. Finally, we summarize current challenges and point out future trends of deep learning in sports. Our survey provides valuable reference material for researchers interested in deep learning in sports applications.
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2025 1verdicts
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FSBench: A Figure Skating Benchmark for Advancing Artistic Sports Understanding
A new figure skating dataset and benchmark, FSAnno and FSBench, evaluates and improves multimodal large language models on technical and artistic understanding of figure skating.