Submissions regarding the analysis and understanding of images/videos acquired during winter activities are welcome to our workshop. The following topics serve as examples:
Machine learning solutions for video understanding or activity recognition regarding winter sports
Pose estimation of athletes
Evaluation and measurement of athlete performance
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
There will be two submission tracks: full papers and extended abstracts.
Full paper submissions should propose comprehensive and well-validated solutions, and adhere to the guidelines of standard WACV 2022 submissions (max 8 pages + references). Accepted full papers will be published under the WACV 2022 workshop proceedings and included in IEEE Xplore.
Extended abstracts should be max 4 pages in length (including tables, figures and references) and can describe novel but not extensively validated ideas, ongoing works, or be recaps of recently published papers (either journal or conference). The accepted abstracts will be published under an arXiv compendium.
All submissions should be compiled for double-blind review, adopt the standard WACV 2022 template, and be submitted via the workshop's CMT platform:
Please select the appropriate track for your submission ("Full Papers" or "Extended Abstracts").