most citedA Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks

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cs.CV2023

Generating Transferable and Stealthy Adversarial Patch via Attention-guided Adversarial Inpainting

Yanjie Li, Mingxing Duan, Xuelong Dai +1

Adversarial patch attacks can fool the face recognition (FR) models via small patches. However, previous adversarial patch attacks often result in unnatural patterns that are easil…

cs.CV2023★ 2 cited

StyLess: Boosting the Transferability of Adversarial Examples

Kaisheng Liang, Bin Xiao

Adversarial attacks can mislead deep neural networks (DNNs) by adding imperceptible perturbations to benign examples. The attack transferability enables adversarial examples to att…