8th International Workshop on Computer Vision in Sports (CVsports) at CVPR 2022


Please pay attention to this message about CVPR registration:

Each paper (Main Conference AND Workshop)  MUST be registered under a full, in-person registration type. (Student registration type is fine.) One registration may cover multiple papers. Virtual registrations will not cover a paper submission. If circumstances prevent you from attending in person to present your paper, you may attend virtually but you must register and pay for your paper under an in-person registration and please select that you will attend virtually.


List of accepted papers:

  • Ice hockey player identification via transformers and weakly supervised learning. Kanav Vats, William McNally, Pascale Walters, David A Clausi, and John Zelek.
  • Efficient tracking of team sport players with few game-specific annotations. Adrien Maglo, Astrid Orcesi, and Quoc-Cuong Pham
  • 3D Ball Localization From A Single Calibrated Image. Gabriel Van Zandycke, and Christophe De Vleeschouwer
  • Semi-Supervised Training to Improve Player and Ball Detection in Soccer. Renaud Vandeghen, Anthony Cioppa, and Marc Van Droogenbroeck
  • SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos. Anthony Cioppa, Silvio Giancola, Adrien Deliege, Le Kang, Xin Zhou, Zhiyu Cheng, Bernard Ghanem, and Marc Van Droogenbroeck
  • Pass Receiver Prediction in Soccer using Video and Players’ Trajectories. Yutaro Honda, Rei Kawakami, Ryota Yoshihashi, Kenta Kato, and Takeshi Naemura
  • MonoTrack: Shuttle trajectory reconstruction from monocular badminton video. Paul Liu and Jui-Hsien Wang
  • Sports Field Registration via Keypoints-aware Label Condition. Yen-Jui Chu, Jheng-Wei Su, Kai-Wen Hsiao, Chi-Yu Lien, Shu-Ho Fan, Min-Chun Hu, Ruen-Rone Lee, Chih-Yuan Yao, and Hung-Kuo Chu
  • Recognition of Freely Selected Keypoints on Human Limbs. Katja Ludwig, Daniel Kienzle, and Rainer Lienhart
  • Pose Tutor: An Explainable System for Pose Correction in the Wild. Bhat Dittakavi, Bharathi Callepalli, Sai Vikas Desai, Divyagna Bavikadi, Soumi Chakraborty, Nishant S Reddy, Ayon Sharma, and Vineeth N Balasubramanian
  • End-to-End High-Risk Tackle Detection System for Rugby. Naoki Nonaka, Ryo Fujihira, Monami Nishio, Hidetaka Murakami, Takuya Tajima, Mutsuo Yamada, Akira Maeda, and Jun Seita
  • Watch and Act: Dual Interacting Agents for Automatic Generation of Possession Statistics in Soccer. Saikat Sarkar, Dipti Prasad Mukherjee, and Amlan Chakrabarti
  • SoccerTrack: A Dataset and Tracking Algorithm for Soccer with Fish-eye and Drone Videos. Atom Scott, Ikuma Uchida, Masaki Onishi, Yoshinari Kameda, Kazuhiro Fukui, and Keisuke Fujii
  • Interaction Classification with Key Actor Detection in Multi-Person Sports Videos. Farzaneh Askari, Rohit Ramaprasad, James J. Clark, and Martin D. Levine
  • FenceNet: Fine-grained Footwork Recognition in Fencing. Kevin Zhu, Alexander Wong, John McPhee



Sports is said to be the social glue of society. It allows people to interact irrespective of their social status, age etc. With the rise of the mass media, a significant quantity of resources has been channeled into sports in order to improve understanding, performance and presentation. For example, areas like performance assessment, which were previously mainly of interest to coaches and sports scientists are now finding applications in broadcast and other media, driven by the increasing use of on-line sports viewing which provides a way of making all sorts of performance statistics available to viewers. Computer vision has recently started to play an important role in sports as seen in for example football where computer vision-based graphics in real-time enhances different aspects of the game. Computer vision algorithms have a huge potential in many aspects of sports ranging from automatic annotation of broadcast footage, through to better understand of sport injuries, and enhanced viewing. So far, the use of computer vision in sports has been scattered between different disciplines.


Call for papers

The ambition of this workshop is to bring together practitioners and researchers from different disciplines to share ideas and methods on current and future use of computer vision in sports. To this end we welcome computer vision-based research contributions as well as best-practice contributions focusing on the following (and similar) topics:

  • estimation of position and motion of cameras and participants in sports
  • tracking people and objects in sports
  • activity recognition in sports
  • event detection in sports
  • spectator monitoring
  • annotation and indexing in sports
  • graphical effects in sports
  • analysis of injuries in sports
  • performance assessment in sports
  • alternative sensing in sports (beyond the visible spectrum)
  • tactics analysis in sports
  • automatic narration and captioning in sports
  • training assistance in sports
  • augmented/virtual reality in sports
  • datasets in sports
  • bias in sports
  • XAI in sports
  • ethics & algorithms in sports


Important dates

  • Paper submission deadline: March 4 March 14, 2022 (11.59pm Pacific Time)
  • Notification of acceptance: March 22, April 1, 2022
  • Camera ready deadline: April 6 April16, 2022
  • Workshop date: June 20, 2022


Submission instructions

Policies and guidelines (same as for CVPR): Link

Submission: Link

Accepted papers will be published in the CVPR workshop proceedings on IEEE Xplore and as open access on http://openaccess.thecvf.com/.


Best paper award

1000$ sponsored by EVS Broadcast Equipment.


Invited speakers

  • Patrick Lucey, Chief Scientist at Stats Perform
  • Luke Bornn, Co-founder and Chief Scientist at Zelus Analytics
  • Floriane Magera, Data Scientist at EVS Broadcast Equipment and Olivier Barnich, Head of Innovation at EVS Broadcast Equipment
  • Silvio Giancola, Research Scientist at King Abdullah University of Science and Technology (KAUST)

Competition – SoccerNet calibration challenge

Participate in the upcoming calibration challenge at the CVSports workshop at CVPR 2022 and try to win up to 1000$ sponsored by EVS Broadcast Equipment! The participation deadline is fixed at the 30th of May 2022.

Camera calibration is the link between the image world and the 3D real world. Automatic calibration of the camera is an important topic of research for sports analytics that can lead to interesting applications such as offline line analysis. It is also the key to integrate reality graphics into any live production. In this challenge, you may choose to tackle two tasks:

  • Soccer pitch marking and goal post localization: given an image, detect the extremities of every soccer pitch element captured in the image. A soccer pitch element is either a pitch line marking or a goal post part.
  • Automatic camera calibration: given a common 3D pitch template, the camera parameters are used to estimate the reprojection error induced by the camera parameters.

More details may be found on https://www.soccer-net.org/tasks/calibration
Sample code with a first baseline may be found here: https://github.com/SoccerNet/sn-calibration.
The official rules and guidelines are available here: https://github.com/SoccerNet/sn-calibration/blob/main/ChallengeRules.md
and the evaluation server to participate is available at the following address: https://eval.ai/web/challenges/challenge-page/1537/overview

Good luck!



Rikke Gade, Aalborg University, Denmark
Thomas Moeslund, Aalborg University, Denmark
Graham Thomas, BBC, UK
Adrian Hilton, University of Surrey, UK
Jim Little, University of British Columbia, Canada
Michele Merler, IBM Research, USA


Previous editions of CVsports:


Related publications:


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