15 citations · 26 across the 11 of their papers we have counts for
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cs.CV2021★ 15 cited
Towards Defending against Adversarial Examples via Attack-Invariant Features
Dawei Zhou, Tongliang Liu, Bo Han +3
Deep neural networks (DNNs) are vulnerable to adversarial noise. Their adversarial robustness can be improved by exploiting adversarial examples. However, given the continuously ev…
cs.CV2021★ 1 cited
Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training
Dawei Zhou, Nannan Wang, Xinbo Gao +4
Deep neural networks (DNNs) are vulnerable to adversarial noise. A range of adversarial defense techniques have been proposed to mitigate the interference of adversarial noise, amo…
cs.LG2021
Removing Adversarial Noise in Class Activation Feature Space
Dawei Zhou, Nannan Wang, Chunlei Peng +4
Deep neural networks (DNNs) are vulnerable to adversarial noise. Preprocessing based defenses could largely remove adversarial noise by processing inputs. However, they are typical…