1k citations · 2.9k across the 16 of their papers we have counts for
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Unrestricted Adversarial Attacks on ImageNet Competition
Yuefeng Chen, Xiaofeng Mao, Yuan He +34
Many works have investigated the adversarial attacks or defenses under the settings where a bounded and imperceptible perturbation can be added to the input. However in the real-wo…
You Cannot Easily Catch Me: A Low-Detectable Adversarial Patch for Object Detectors
Zijian Zhu, Hang Su, Chang Liu +2
Blind spots or outright deceit can bedevil and deceive machine learning models. Unidentified objects such as digital "stickers," also known as adversarial patches, can fool facial…
Improving the Robustness of Adversarial Attacks Using an Affine-Invariant Gradient Estimator
Wenzhao Xiang, Hang Su, Chang Liu +2
As designers of artificial intelligence try to outwit hackers, both sides continue to hone in on AI's inherent vulnerabilities. Designed and trained from certain statistical distri…
Improving Visual Quality of Unrestricted Adversarial Examples with Wavelet-VAE
Wenzhao Xiang, Chang Liu, Shibao Zheng
Traditional adversarial examples are typically generated by adding perturbation noise to the input image within a small matrix norm. In practice, un-restricted adversarial attack h…