mlsanityData to 7 Oct 2026

A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision

arXiv 2307.03353 ↗First posted 7 Jul 2023cs.CVcited by 11

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Abstract (arXiv)

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.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 174 of its 344 references that are in the map. First posted on arXiv 7 Jul 2023.

Builds on

174 of 344 references.

References · 174

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50 most cited of 174 All 174 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 4; 2025: 2; 2026: 2.

11 papers.

  1. 2023See and Think: Embodied Agent in Virtual Environmentcited by 54
  2. 2024Language and Multimodal Models in Sports: A Survey of Datasets and Applicationscited by 10
  3. 2024ETTrack: Enhanced Temporal Motion Predictor for Multi-Object Trackingcited by 9
  4. 2023Efficient Domain Adaptation via Generative Prior for 3D Infant Pose Estimationcited by 8
  5. 2024Deep learning for action spotting in association football videoscited by 7
  6. 2025FSBench: A Figure Skating Benchmark for Advancing Artistic Sports Understandingcited by 6
  7. 2025Deep Learning for Sports Video Event Detection: Tasks, Datasets, Methods, and Challengescited by 3
  8. 2023UniHPE: Towards Unified Human Pose Estimation via Contrastive Learningcited by 2
  9. 2024SportsNGEN: Sustained Generation of Realistic Multi-player Sports Gameplaycited by 0
  10. 2026Group-DINOmics: Incorporating People Dynamics into DINO for Self-supervised Group Activity Feature Learningcited by 0
  11. 2026A Survey of Large Models in Sportscited by 0