SoccerNet 2023 Challenges Results
Anthony Cioppa Silvio Giancola Vladimir Somers Floriane Magera Xin Zhou Hassan Mkhallati Adrien 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 Chen Chen Fabian Deuser Feng Yan Fufu Yu Gal Shitrit Guanshuo Wang Gyusik Choi Hankyul Kim Hao Guo Hasby Fahrudin Hidenari Koguchi Håkan Ardö Ibrahim Salah Ido Yerushalmy Iftikar Muhammad Ikuma Uchida Ishay Be'ery Jaonary Rabarisoa Jeongae Lee Jiajun Fu Jianqin Yin Jinghang Xu Jongho Nang Julien Denize Junjie 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 Mohamed Abdelwahed Mykola Liashuha Nikolay Falaleev Norbert Oswald Qiong Jia Quoc-Cuong Pham Ran Song Romain Hérault Rui Peng Ruilong Chen Ruixuan Liu Ruslan Baikulov Ryuto Fukushima Sergio Escalera Seungcheon Lee Shimin Chen Shouhong Ding Taiga Someya Thomas B. Moeslund Tianjiao Li Wei Shen Wei Zhang Wei Li Wei Dai Weixin Luo Wending Zhao Wenjie Zhang Xinquan Yang Yanbiao Ma Yeeun Joo Yingsen Zeng Yiyang Gan Yongqiang Zhu Yujie Zhong Zheng Ruan Zhiheng Li Zhijian Huang Ziyu Meng
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.