Dong Kyu Cho

PEER Pressure: Model-to-Model Regularization for Single Source Domain Generalization

Data augmentation is a popular tool for single source domain generalization, which expands the source domain by generating simulated ones, improving generalization on unseen target domains. In this work, we show that the performance of such augmentation-based methods in the target domains universall…