Technical Report for ICCV 2023 Visual Continual Learning Challenge: Continuous Test-time Adaptation for Semantic Segmentation

no code implementations • 20 Oct 2023 • Damian Sójka, Yuyang Liu, Dipam Goswami, Sebastian Cygert, Bartłomiej Twardowski, Joost Van de Weijer

Each sequence is composed of 401 images and starts with the source domain, then gradually drifts to a different one (changing weather or time of day) until the middle of the sequence.

Continual Learning Semantic Segmentation +1

AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation

no code implementations • 18 Sep 2023 • Damian Sójka, Sebastian Cygert, Bartłomiej Twardowski, Tomasz Trzciński

Test-time adaptation is a promising research direction that allows the source model to adapt itself to changes in data distribution without any supervision.

Autonomous Driving Test-time Adaptation