most citedDeep learning for action spotting in association football videos

4 citations · 5 across the 6 of their papers we have counts for

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cs.CV2025

Pixels or Positions? Benchmarking Modalities in Group Activity Recognition

Drishya Karki, Merey Ramazanova, Anthony Cioppa +2

Group Activity Recognition (GAR) is well studied on the video modality for surveillance and indoor team sports (e.g., volleyball, basketball). Yet, other modalities such as agent p…

cs.CV2025

SoccerNet 2025 Challenges Results

Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115

The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…

cs.CV2025

Triangle Splatting for Real-Time Radiance Field Rendering

Jan Held, Renaud Vandeghen, Adrien Deliege +7

The field of computer graphics was revolutionized by models such as Neural Radiance Fields and 3D Gaussian Splatting, displacing triangles as the dominant representation for photog…

cs.CV2025

Action Anticipation from SoccerNet Football Video Broadcasts

Mohamad Dalal, Artur Xarles, Anthony Cioppa +6

Artificial intelligence has revolutionized the way we analyze sports videos, whether to understand the actions of games in long untrimmed videos or to anticipate the player's motio…

cs.CV2024

3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes

Jan Held, Renaud Vandeghen, Abdullah Hamdi +6

Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes wi…

cs.CV2024★ 4 cited

Deep learning for action spotting in association football videos

Silvio Giancola, Anthony Cioppa, Bernard Ghanem +1

The task of action spotting consists in both identifying actions and precisely localizing them in time with a single timestamp in long, untrimmed video streams. Automatically extra…