ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries

Understand

Zero-shot learning (ZSL) has received extensive attention recently especially in areas of fine-grained object recognition, retrieval, and image captioning.

• Due to the complete lack of training samples and high requirement of defense transferability, the ZSL model learned is particularly vulnerable against adversarial attacks.
• Recent work also showed adversarially robust generalization requires more data.
• This may significantly affect the robustness of ZSL.