Winter sports such as skiing, bobsleigh, ice-skating, and ice hockey are popular winter activities. To improve human well-being and sociality, different winter sports federations want to promote such sports by increasing people's engagement in them. This is mostly obtained by the broadcasting of professional competitions. Indeed, the TV transmission of only alpine and nordic skiing competitions attracts around 6 billion viewers (source: International Ski Federation – FIS - 2019/2020 season reports) including many new potential practitioners.

Increased interest in the winter disciplines can be achieved by enhancing the viewing experience of the spectators through richer broadcasting content and higher athlete performance, and yet-to-come video technologies can drive these. The most common solutions available today to analyze athlete performance are based on sensors like IMUs or GNSS. Image and video analytics is not a predominant technology in the winter sports domain yet, even though a large amount of visual data is available through broadcast videos or can be generated at a cheap cost with standard cameras. We believe this gap is partly due to the challenging settings that snow and ice sports offer. Winter disciplines provide particular application scenarios where the performance is executed at high speed, on varying and unconstrained terrains, by controlling some kind of object, and under difficult weather conditions. These challenges must be then considered in relation to the real-time processing requirements of broadcasting or the decision-making processes performed during the training. We believe that the problems in these domains offer stimulating questions that would lead to relevant contributions to the computer vision field.

For these motivations, the goal of our workshop is twofold: on one hand to promote the employment of computer vision and AI solutions in the winter sports industry, by presenting the latest research solutions for winter sports-related problems; and at the same time, we would like to stimulate the interest of the computer vision and AI audience with new and interesting problems that could lead to the engagement of researchers and the development of new solutions. Hence, we invite researchers and engineers interested in these topics to join our workshop, submitting ongoing and recently published ideas, demos, and applications in support of increasing the effectiveness and efficiency of computer vision technologies in the winter sports domain.

Call for Papers

Research papers are solicited in, but not limited to, the following topic areas:

  • Machine learning solutions for video understanding or activity recognition regarding winter sports

  • Pose estimation of athletes

  • Evaluation and measurement of athlete performance

  • Performance forecasting

  • Detection/evaluation/prevention of injuries in winter sports with computer vision

  • Crowd and spectators monitoring

  • Augmented/virtual reality for winter sports and fan engagement

  • Applications of computer vision/AI to winter sports (skiing, ice-hockey, ice-skating, biathlon, bobsleigh, luge, curling, etc.)

  • Image/video understanding in winter/harsh weather conditions

  • Camera pose estimation in broadcast videos

  • Video-based trajectory reconstruction and analysis

  • Winter scene reconstruction from images/videos

  • Snow/ice measurements and analysis with computer vision

  • Real-time processing algorithms

  • Fusion of image/video data and other sensor data

  • Datasets, benchmarks and annotations of winter sport data

Please see the Submissions and Dates page for details about the submissions.

Invited Speakers

Coming soon!

Supporting Organizations