December 3rd, 2024 
Daniela Lopez de Luise SKITB VISUAL TRACKING CHALLENGE
at the 3rd Workshop on Computer Vision for Winter Sports (CV4WS)
https://sites.google.com/unitn.it/cv4ws-wacv2025
in conjunction with
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2025
(https://wacv2025.thecvf.com/)
in conjunction with
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2025
(https://wacv2025.thecvf.com/)
CHALLENGE WEBSITE
OVERVIEW
We are excited to announce the SkiTB Visual Tracking Challenge, part of the CV4WS workshop at WACV 2025. This challenge focuses on tracking skiers' performances across multiple camera views in complex, real-world winter sports environments. Participants will design trackers capable of following a skier throughout a performance, starting with the bounding box in the first frame and localizing the skier in all subsequent frames.
The challenge leverages the SkiTB dataset, featuring: 300 multi-camera professional skiing videos; 352,978 annotated frames; Full HD videos in dynamic, snowy outdoor environments. This dataset offers a unique opportunity to test tracking models on complex scenarios typical of winter sports.
IMPORTANT DATES
- December 1, 2024: challenge open
- January 31, 2025: submission due
- February 7, 2025: technical report due
Workshop date:
- February 28 or March 3 or 4, 2025
PARTICIPATION
Detailed instructions on how to participate are available on the challenge page:
We encourage researchers and practitioners in computer vision to participate in this exciting challenge. Selected teams will be invited to present their solutions at the workshop, with opportunities for further publication in a special journal issue.
We look forward to your submissions!
ORGANIZERS
Dr. Niccolò Bisagno, University of Trento, Italy
Dr. Matteo Dunnhofer, University of Udine, Italy
Dr. Katja Ludwig, University of Augsburg, Germany
Prof. Hideki Koike, Tokyo Institute of Technology, Japan
Prof. Christian Micheloni, University of Udine, Italy
Prof. Nicola Conci, University of Trento, Italy
Computer Vision and Machine Learning (CVML) email list www page: https://lists.auth.gr/sympa/info/cvml
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