3 papers
cs.CV2024
Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised Domain Generalization
Adnan Khan, Mai A. Shaaban, Muhammad Haris Khan
Beyond attaining domain generalization (DG), visual recognition models should also be data-efficient during learning by leveraging limited labels. We study the problem of Semi-Supe…
cs.CV2024
Domain-Guided Weight Modulation for Semi-Supervised Domain Generalization
Chamuditha Jayanaga Galappaththige, Zachary Izzo, Xilin He +2
Unarguably, deep learning models capable of generalizing to unseen domain data while leveraging a few labels are of great practical significance due to low developmental costs. In…
cs.CV2024
Towards Generalizing to Unseen Domains with Few Labels
Chamuditha Jayanga Galappaththige, Sanoojan Baliah, Malitha Gunawardhana +1
We approach the challenge of addressing semi-supervised domain generalization (SSDG). Specifically, our aim is to obtain a model that learns domain-generalizable features by levera…