mlsanityData to 7 Oct 2026

OSL-ActionSpotting: A Unified Library for Action Spotting in Sports Videos

arXiv 2407.01265 ↗First posted 1 Jul 2024cs.CVcited by 2

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Abstract (arXiv)

Action spotting is crucial in sports analytics as it enables the precise identification and categorization of pivotal moments in sports matches, providing insights that are essential for performance analysis and tactical decision-making. The fragmentation of existing methodologies, however, impedes the progression of sports analytics, necessitating a unified codebase to support the development and deployment of action spotting for video analysis. In this work, we introduce OSL-ActionSpotting, a Python library that unifies different action spotting algorithms to streamline research and applications in sports video analytics. OSL-ActionSpotting encapsulates various state-of-the-art techniques into a singular, user-friendly framework, offering standardized processes for action spotting and analysis across multiple datasets. We successfully integrated three cornerstone action spotting methods into OSL-ActionSpotting, achieving performance metrics that match those of the original, disparate codebases. This unification within a single library preserves the effectiveness of each method and enhances usability and accessibility for researchers and practitioners in sports analytics. By bridging the gaps between various action spotting techniques, OSL-ActionSpotting significantly contributes to the field of sports video analysis, fostering enhanced analytical capabilities and collaborative research opportunities. The scalable and modularized design of the library ensures its long-term relevance and adaptability to future technological advancements in the domain.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 29 of its 47 references that are in the map. First posted on arXiv 1 Jul 2024.

Builds on

29 of 47 references.

References · 29

  1. 2014On the Properties of Neural Machine Translation: Encoder-Decoder Approachescited by 1,303
  2. 2018SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videoscited by 148
  3. 2020SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videoscited by 129
  4. 2022SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videoscited by 80
  5. 2019Gate-Shift Networks for Video Action Recognitioncited by 76
  6. 2022Body Part-Based Representation Learning for Occluded Person Re-Identificationcited by 63
  7. 2023SoccerNet-Caption: Dense Video Captioning for Soccer Broadcasts Commentariescited by 57
  8. 2019A Context-Aware Loss Function for Action Spotting in Soccer Videoscited by 56
  9. 2021Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spottingcited by 43
  10. 2022Spotting Temporally Precise, Fine-Grained Events in Videocited by 40
  11. 2023VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Viewscited by 38
  12. 2024SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a Minimapcited by 34
17 more
  1. 2021Temporally-Aware Feature Pooling for Action Spotting in Soccer Broadcastscited by 30
  2. 2022SoccerNet 2022 Challenges Resultscited by 28
  3. 2022Temporally Precise Action Spotting in Soccer Videos Using Dense Detection Anchorscited by 27
  4. 2022A Survey on Video Action Recognition in Sports: Datasets, Methods and Applicationscited by 27
  5. 2022Semi-Supervised Training to Improve Player and Ball Detection in Soccercited by 25
  6. 2022MonoTrack: Shuttle trajectory reconstruction from monocular badminton videocited by 24
  7. 2024X-VARS: Introducing Explainability in Football Refereeing with Multi-Modal Large Language Modelcited by 22
  8. 2020Improved Soccer Action Spotting using both Audio and Video Streamscited by 21
  9. 2022A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directionscited by 21
  10. 2020Using Player's Body-Orientation to Model Pass Feasibility in Soccercited by 20
  11. 2021RMS-Net: Regression and Masking for Soccer Event Spottingcited by 19
  12. 2020Event detection in coarsely annotated sports videos via parallel multi receptive field 1D convolutionscited by 18
  13. 2022Ball 3D Localization From A Single Calibrated Imagecited by 17
  14. 2022Efficient tracking of team sport players with few game-specific annotationscited by 17
  15. 2023COMEDIAN: Self-Supervised Learning and Knowledge Distillation for Action Spotting using Transformerscited by 17
  16. 2024A Universal Protocol to Benchmark Camera Calibration for Sportscited by 14
  17. 2022A Graph-Based Method for Soccer Action Spotting Using Unsupervised Player Classificationcited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 0; 2026: 1.

2 papers.

  1. 2024Deep learning for action spotting in association football videoscited by 7
  2. 2026BMASH: Ball-Motion-Aware Soccer Header Spottingcited by 0