mlsanityData to 7 Oct 2026

RMS-Net: Regression and Masking for Soccer Event Spotting

arXiv 2102.07624 ↗First posted 15 Feb 2021cs.CVcited by 19

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Abstract (arXiv)

The recently proposed action spotting task consists in finding the exact timestamp in which an event occurs. This task fits particularly well for soccer videos, where events correspond to salient actions strictly defined by soccer rules (a goal occurs when the ball crosses the goal line). In this paper, we devise a lightweight and modular network for action spotting, which can simultaneously predict the event label and its temporal offset using the same underlying features. We enrich our model with two training strategies: the first one for data balancing and uniform sampling, the second for masking ambiguous frames and keeping the most discriminative visual cues. When tested on the SoccerNet dataset and using standard features, our full proposal exceeds the current state of the art by 3 Average-mAP points. Additionally, it reaches a gain of more than 10 Average-mAP points on the test set when fine-tuned in combination with a strong 2D backbone.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 24 of its 34 references that are in the map. First posted on arXiv 15 Feb 2021.

Builds on

24 of 34 references.

References · 24

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12 more
  1. 2016YouTube-8M: A Large-Scale Video Classification Benchmarkcited by 324
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  6. 2016Spatiotemporal Residual Networks for Video Action Recognitioncited by 91
  7. 2016Long-term Temporal Convolutions for Action Recognitioncited by 84
  8. 2019A Context-Aware Loss Function for Action Spotting in Soccer Videoscited by 56
  9. 2019A Multigrid Method for Efficiently Training Video Modelscited by 52
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  11. 2020Event detection in coarsely annotated sports videos via parallel multi receptive field 1D convolutionscited by 18
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Built on by

Cited by year

Citing papers per year: 2021: 3; 2022: 5; 2023: 3; 2024: 3; 2025: 5.

19 papers.

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  1. 2021Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spottingcited by 43
  2. 2022Spotting Temporally Precise, Fine-Grained Events in Videocited by 40
  3. 2021Temporally-Aware Feature Pooling for Action Spotting in Soccer Broadcastscited by 30
  4. 2022Temporally Precise Action Spotting in Soccer Videos Using Dense Detection Anchorscited by 27
  5. 2023COMEDIAN: Self-Supervised Learning and Knowledge Distillation for Action Spotting using Transformerscited by 17
  6. 2022Action Spotting using Dense Detection Anchors Revisited: Submission to the SoccerNet Challenge 2022cited by 14
  7. 2023Towards Active Learning for Action Spotting in Association Football Videoscited by 14
  8. 2022A Graph-Based Method for Soccer Action Spotting Using Unsupervised Player Classificationcited by 10
  9. 2025Action Anticipation from SoccerNet Football Video Broadcastscited by 9
  10. 2024Unifying Global and Local Scene Entities Modelling for Precise Action Spottingcited by 8
  11. 2023Survey of Action Recognition, Spotting and Spatio-Temporal Localization in Soccer -- Current Trends and Research Perspectivescited by 7
  12. 2024Deep learning for action spotting in association football videoscited by 7
7 more
  1. 2025Precise Event Spotting in Sports Videos: Solving Long-Range Dependency and Class Imbalancecited by 6
  2. 2021A Unified Taxonomy and Multimodal Dataset for Events in Invasion Gamescited by 4
  3. 2022Deep soccer captioning with transformer: dataset, semantics-related losses, and multi-level evaluationcited by 4
  4. 2025Deep Learning for Sports Video Event Detection: Tasks, Datasets, Methods, and Challengescited by 3
  5. 2024OSL-ActionSpotting: A Unified Library for Action Spotting in Sports Videoscited by 2
  6. 2025Do We Need Large VLMs for Spotting Soccer Actions?cited by 1
  7. 2025TrajSV: A Trajectory-based Model for Sports Video Representations and Applicationscited by 0