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SoccerNet 2023 Challenges Results

12 September 2023
A. Cioppa
Silvio Giancola
Vladimir Somers
Floriane Magera
Xinxing Zhou
Hassan Mkhallati
A. Deliège
Jan Held
Carlos Hinojosa
Amir M. Mansourian
Pierre Miralles
Olivier Barnich
Christophe De Vleeschouwer
Alexandre Alahi
Bernard Ghanem
Marc Van Droogenbroeck
Abdullah Kamal
Adrien Maglo
Albert Clapés
Amr Abdelaziz
Artur Xarles
Astrid Orcesi
Atom Scott
Bin Liu
Byoungkwon Lim
C. L. P. Chen
Fabian Deuser
Feng Yan
Fufu Yu
Gal Shitrit
Guanshuo Wang
Gyusik Choi
H. Kim
Hao Guo
Hasby Fahrudin
Hidenari Koguchi
Haakan Ardo
Ibrahim Salah
Ido Yerushalmy
Iftikar Muhammad
Ikuma Uchida
Ishay Beéry
Jaonary Rabarisoa
Jeongae Lee
Jiajun Fu
Jianqin Yin
Jinghang Xu
Jongho Nang
J. Denize
Jianing Li
Junpei Zhang
Juntae Kim
Kamil Synowiec
Kenji Kobayashi
Kexin Zhang
Konrad Habel
Kota Nakajima
Licheng Jiao
Lin Ma
Lizhi Wang
Luping Wang
Menglong Li
Mengying Zhou
Mohamed Nasr
M. Abdelwahed
Mykola Liashuha
Nikolay S Falaleev
Norbert Oswald
Qi Jia
Quoc-Cuong Pham
Ran Song
Romain Hérault
Rui Peng
Ruilong Chen
Ruixuan Liu
Ruslan Baikulov
Ryuto Fukushima
Sergio Escalera
Seungcheon Lee
Shi-Jin Chen
Shouhong Ding
Taiga Someya
T. Moeslund
Tianjiao Li
Wei Shen
Wei Zhang
Wei Li
Wei-Ming Dai
Weihua Luo
Wending Zhao
W. Zhang
Xinquan Yang
Yanbiao Ma
Yeeun Joo
Yingsen Zeng
Yiyang Gan
Yongqiang Zhu
Yujie Zhong
Zheng Ruan
Zhiheng Li
Zhijian Huang
Ziyu Meng
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Abstract

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 vision-based tasks split into three main themes. The first theme, broadcast video understanding, is composed of three high-level tasks related to describing events occurring in the video broadcasts: (1) action spotting, focusing on retrieving all timestamps related to global actions in soccer, (2) ball action spotting, focusing on retrieving all timestamps related to the soccer ball change of state, and (3) dense video captioning, focusing on describing the broadcast with natural language and anchored timestamps. The second theme, field understanding, relates to the single task of (4) camera calibration, focusing on retrieving the intrinsic and extrinsic camera parameters from images. The third and last theme, player understanding, is composed of three low-level tasks related to extracting information about the players: (5) re-identification, focusing on retrieving the same players across multiple views, (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams, and (7) jersey number recognition, focusing on recognizing the jersey number of players from tracklets. Compared to the previous editions of the SoccerNet challenges, tasks (2-3-7) are novel, including new annotations and data, task (4) was enhanced with more data and annotations, and task (6) now focuses on end-to-end approaches. More information on the tasks, challenges, and leaderboards are available on https://www.soccer-net.org. Baselines and development kits can be found on https://github.com/SoccerNet.

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