Vision-language pre-trained (VLP) models have been the foundation of numerous vision-
language tasks. Given their prevalence, it becomes imperative to assess their adversarial …

Abstract Generalized Zero-Shot Learning (GZSL) methods often assume that the unseen
classes are similar to seen classes and thus perform poor when unseen classes are …

Zero-Shot learning (ZSL) correlates visual samples and shared semantic information to
transfer knowledge from seen classes to unseen classes. Existing methods typically …

Generalized zero-shot learning (GZSL) is a further extension of the zero-shot learning field,
aiming to address the problem of simultaneous classification of known and unknown …

Zero-shot learning (ZSL) aims to recognize new classes without prior exposure to their
samples, relying on semantic knowledge from observed classes. However, current attention …

The goal of zero-shot learning is to utilize attribute information for seen classes so as to
generalize the learned knowledge to unseen classes. However, current algorithms often …