Abstract: Few-shot learning (FSL) facilitates a variety of computer vision tasks yet remains vulnerable to adversarial attacks. Existing adversarially robust FSL methods rely on either visual ...

Abstract: Non-exemplar class-incremental learning refers to continual classifying of new and old classes without storing samples of old classes. Since only new class samples are available, ...