Transferable Semantic Augmentation for Domain Adaptation
Transferable Semantic Augmentation for Domain Adaptation
Domain adaptation has been widely explored by transferring the knowledge from a label-rich source domain to a related but unlabeled target domain. Most existing domain adaptation algorithms attend to adapting feature representations across two domains with the guidance of a shared source-supervised classifier. However, such classifier limits the generalization ability …