SoccerNet 2022 Challenges Results

challenge; dataset; SoccerNet; video understanding; sports; soccer; neural netwok; artificial intelligence; human tracking; player tracking; machine learning; deep learning; Sport; Football

Abstract :

[en] The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks: (1) action spotting, focusing on retrieving action timestamps in long untrimmed videos, (2) replay grounding, focusing on retrieving the live moment of an action shown in a replay, (3) pitch localization, focusing on detecting line and goal part elements, (4) camera calibration, dedicated to retrieving the intrinsic and extrinsic camera parameters, (5) player re-identification, focusing on retrieving the same players across multiple views, and (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams. Compared to last year's challenges, tasks (1-2) had their evaluation metrics redefined to consider tighter temporal accuracies, and tasks (3-6) were novel, including their underlying data and annotations. More information on the tasks, challenges and leaderboards are available on https://www.soccer-net.org. Baselines and development kits are available on https://github.com/SoccerNet .

Research Center/Unit :

Telim
Montefiore

Disciplines :

Electrical & electronics engineering

Author, co-author :

Giancola, Silvio ^✱; KAUST, Thuwal, Saudi Arabia

Cioppa, Anthony ^✱; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science

Deliège, Adrien ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Télécommunications

Magera, Floriane ; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science

Somers, Vladimir; Sportradar, UCLouvain, & EPFL, Minneapolis, MN, USA

Kang, Le; Baidu Research, Seattle, WA, USA

Zhou, Xin; Baidu Research, Seattle, WA, USA

Barnich, Olivier; EVS Broadcast Equipment, Seraing, Belgium

De Vleeschouwer, Christophe; UCLouvain, Louvain-la-Neuve, Belgium

Alahi, Alexandre; EPFL, Lausanne, Switzerland

More authors (84 more)

^✱ These authors have contributed equally to this work.

Language :

English

Title :

SoccerNet 2022 Challenges Results

Publication date :

10 October 2022

Event name :

5th International ACM Workshop on Multimedia Content Analysis in Sports (MMSports)

Event organizer :

ACM

Event place :

Lisboa, Portugal

Event date :

10/10/2022

Audience :

International

Main work title :

ACM International Conference on Multimedia

Publisher :

Association for Computing Machinery, New York, United States - New York

Pages :

75-86

Peer reviewed :

Peer reviewed

Name of the research project :

Applications et Recherche pour une Intelligence Artificielle de Confiance (ARIAC)

Funders :

SPW - Public Service of Wallonia

Funding number :

2010235

Data Set :

https://www.soccer-net.org/

Available on ORBi :

since 04 November 2022

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