74 citations · 78 across the 6 of their papers we have counts for
5 papers · 1 filter
Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective
Yao Zhu, Yuefeng Chen, Xiaodan Li +6
Transferable adversarial attacks against Deep neural networks (DNNs) have received broad attention in recent years. An adversarial example can be crafted by a surrogate model and t…
Invertible Mask Network for Face Privacy-Preserving
Yang Yang, Yiyang Huang, Ming Shi +3
Face privacy-preserving is one of the hotspots that arises dramatic interests of research. However, the existing face privacy-preserving methods aim at causing the missing of seman…
Adversarial Examples Detection beyond Image Space
Kejiang Chen, Yuefeng Chen, Hang Zhou +4
Deep neural networks have been proved that they are vulnerable to adversarial examples, which are generated by adding human-imperceptible perturbations to images. To defend these a…
LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud-based Deep Networks
Hang Zhou, Dongdong Chen, Jing Liao +6
Deep neural networks have made tremendous progress in 3D point-cloud recognition. Recent works have shown that these 3D recognition networks are also vulnerable to adversarial samp…
DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense
Hang Zhou, Kejiang Chen, Weiming Zhang +3
Neural networks are vulnerable to adversarial examples, which poses a threat to their application in security sensitive systems. We propose a Denoiser and UPsampler Network (DUP-Ne…