2022年足球网 (SoccerNet 2022 Challenges Results)

Silvio Giancola,Anthony Cioppa,Adrien Deliège,Floriane Magera,Vladimir Somers,Le Kang,Xin Zhou,Olivier Barnich,Christophe De Vleeschouwer,Alexandre Alahi,Bernard Ghanem,Marc Van Droogenbroeck,Abdulrahman Darwish,Adrien Maglo,Albert Clapés,Andreas Luyts,Andrei Boiarov,Artur Xarles,Astrid Orcesi,Avijit Shah,Baoyu Fan,Bharath Comandur,Chen Chen,Chen Zhang,Chen Zhao,Chengzhi Lin,Cheuk-Yiu Chan,Chun Chuen Hui,Dengjie Li,Fan Yang,Fan Liang,Fang Da,Feng Yan,Fufu Yu,Guanshuo Wang,H. Anthony Chan,He Zhu,Hongwei Kan,Jiaming Chu,Jianming Hu,Jianyang Gu,Jin Chen,João V. B. Soares,Jonas Theiner,Jorge De Corte,José Henrique Brito,Jun Zhang,Junjie Li,Junwei Liang,Leqi Shen,Lin Ma,Lingchi Chen,Miguel Santos Marques,Mike Azatov,Nikita Kasatkin,Ning Wang,Qiong Jia,Quoc Cuong Pham,Ralph Ewerth,Ran Song,Rengang Li,Rikke Gade,Ruben Debien,Runze Zhang,Sangrok Lee,Sergio Escalera,Shan Jiang,Shigeyuki Odashima,Shimin Chen,Shoichi Masui,Shouhong Ding,Sin-wai Chan,Siyu Chen,Tallal El-Shabrawy,Tao He,Thomas B. Moeslund,Wan-Chi Siu,Wei Zhang,Wei Li,Xiangwei Wang,Xiao Tan,Xiaochuan Li,Xiaolin Wei,Xiaoqing Ye,Xing Liu,Xinying Wang,Yandong Guo,Yaqian Zhao,Yi Yu,Yingying Li,Yue He,Yujie Zhong,Zhenhua Guo,Zhiheng Li

from arxiv, Accepted at ACM MMSports 2022

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.

翻译：SoccerNet 2022挑战是SocerNet团队组织的第二次年度视频理解挑战。2022年,挑战由6项基于愿景的任务组成:(1) 行动定位,重点是在长长的未剪辑的视频中检索行动时间戳,(2) 重播地面,重点是检索重播中显示的行动的实况时刻,(3) 投球定位,重点是探测线条和目标部分要素,(4) 摄影校准,专门用于检索内在和外部相机参数,(5) 播放器重新识别,侧重于在多个视图中检索同一批玩家,(6) 多个对象跟踪,重点是通过未经编辑的视频流跟踪玩家和球。与去年的挑战相比,任务(1-2)重新界定其评价指标,以考虑更紧凑的时间分解,任务(3-6)是新奇的,包括基本数据和说明。关于任务、挑战和领导板的更多信息可在https://www.socer-net.org上查阅。基准和发展工具包可在https://github.com/SNetcer.org上查阅。