Concept drift in Object Detection applied to the largest annotated public thermal database Call for Papers
Concept drift in Object Detection applied to the largest annotated public thermal database
Challenge description: The challenge will use an extension of the LTD
Dataset (Nikolov, Ivan Adriyanov, et al. "Seasons in Drift: A
Long-Term Thermal Imaging Dataset for Studying Concept Drift."
NeurIPS, 2021) which consists of thermal footage that spans multiple
seasons. For deployment and long-term use of machine-learning
algorithms in a surveillance context it is vital that the algorithm is
robust to the concept drift that occurs as the conditions in the
outdoor environment changes. This challenge aims to spotlight the
problem of concept drift in a surveillance context and highlight the
challenges and limitations of existing methods. It will be divided
into three competition tracks. Depending on the track chosen the
training data will vary, however the validation and testing data will
remain the same across all challenges.
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/
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 , Computer Vision
Center (CVC) and University of Barcelona, Spain
Kamal Nasrollahi , Milestone Systems and Aalborg
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
Anthony Hoogs, Kitware, USA
Shmuel Peleg, Hebrew University, Israel
Mubarak Shah, University of Central Florida, USA