Track 1 - Detection at day level: Train on a predefined and single day data and evaluate concept drift across time.
Track 2 - Detection at week level: Train on a predefined and single week data and evaluate concept drift across time.
Track 3 - Detection at month level: Train on a predefined and single month data and evaluate concept drift across time.
Challenge webpage: https://chalearnlap.cvc.uab.cat/challenge/51/description/
Tentative Schedule:
Start of the Challenge (development phase): April 25, 2022
Start of test phase: June 17, 2022
End of the Challenge: June 24, 2022
Release of final results: July 1st, 2022
Participants are invited to submit their contributions to the associated ECCV’22 Workshop (https://vap.aau.dk/rws-eccv2022/), independently of their rank position.
ORGANIZATION and CONTACT
Sergio Escalera <sergio.escal...@gmail.com>, Computer Vision Center (CVC) and University of Barcelona, Spain
Kamal Nasrollahi <k...@create.aau.dk>, Milestone Systems and Aalborg University, Denmark
Thomas B. Moeslund, Aalborg University, Aalborg, Denmark
Julio C. S. Jacques Junior, Computer Vision Center (CVC), Spain
Anders Skaarup Johansen, Aalborg University, Denmark
Radu Ionescu, University of Bucharest, Romania
Fahad Shahbaz Khan, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates, and Linköping University, Sweden
Anthony Hoogs, Kitware, USA
Shmuel Peleg, Hebrew University, Israel
Mubarak Shah, University of Central Florida, USA