Publications (10)
Space evaluation based on pitch control using drone video in Ultimate
Shunsuke Iwashita, Atom Scott, Rikuhei Umemoto +2
Ultimate is a sport in which teams of seven players compete for points by passing a disc into the end zone. A distinctive aspect of Ultimate is that the player holding the disc is…
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…
SoccerNet 2023 Challenges Results
Anthony Cioppa, Silvio Giancola, Vladimir Somers +99
The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vi…
Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations
Keisuke Fujii, Kazushi Tsutsui, Atom Scott +3
Modeling of real-world biological multi-agents is a fundamental problem in various scientific and engineering fields. Reinforcement learning (RL) is a powerful framework to generat…
SoccerNet 2026 Challenges Results
Anthony Cioppa, Silvio Giancola, Håkan Ardö +102
The SoccerNet 2026 Challenges constitute the sixth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in sports video underst…
How does AI play football? An analysis of RL and real-world football strategies
Atom Scott, Keisuke Fujii, Masaki Onishi
Recent advances in reinforcement learning (RL) have made it possible to develop sophisticated agents that excel in a wide range of applications. Simulations using such agents can p…
Basketball-SORT: An Association Method for Complex Multi-object Occlusion Problems in Basketball Multi-object Tracking
Qingrui Hu, Atom Scott, Calvin Yeung +1
Recent deep learning-based object detection approaches have led to significant progress in multi-object tracking (MOT) algorithms. The current MOT methods mainly focus on pedestria…
TeamTrack: A Dataset for Multi-Sport Multi-Object Tracking in Full-pitch Videos
Atom Scott, Ikuma Uchida, Ning Ding +7
Multi-object tracking (MOT) is a critical and challenging task in computer vision, particularly in situations involving objects with similar appearances but diverse movements, as s…
SoccerTrack v2: A Full-Pitch Multi-View Soccer Dataset for Game State Reconstruction
Atom Scott, Ikuma Uchida, Kento Kuroda +2
SoccerTrack v2 is a new public dataset for advancing multi-object tracking (MOT), game state reconstruction (GSR), and ball action spotting (BAS) in soccer analytics. Unlike prior…
SoccerNet 2024 Challenges Results
Anthony Cioppa, Silvio Giancola, Vladimir Somers +81
The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team. These challenges aim to advance research across multiple t…