156 citations · 301 across the 25 of their papers we have counts for
4 papers · 1 filter
Towards Open-Set Test-Time Adaptation Utilizing the Wisdom of Crowds in Entropy Minimization
Jungsoo Lee, Debasmit Das, Jaegul Choo +1
Test-time adaptation (TTA) methods, which generally rely on the model's predictions (e.g., entropy minimization) to adapt the source pretrained model to the unlabeled target domain…
Progressive Random Convolutions for Single Domain Generalization
Seokeon Choi, Debasmit Das, Sungha Choi +3
Single domain generalization aims to train a generalizable model with only one source domain to perform well on arbitrary unseen target domains. Image augmentation based on Random…
DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction
Shubhankar Borse, Debasmit Das, Hyojin Park +3
We present DejaVu, a novel framework which leverages conditional image regeneration as additional supervision during training to improve deep networks for dense prediction tasks su…
TransAdapt: A Transformative Framework for Online Test Time Adaptive Semantic Segmentation
Debasmit Das, Shubhankar Borse, Hyojin Park +4
Test-time adaptive (TTA) semantic segmentation adapts a source pre-trained image semantic segmentation model to unlabeled batches of target domain test images, different from real-…