19 citations · 53 across the 8 of their papers we have counts for
8 papers
A Systematical Solution for Face De-identification
Songlin Yang, Wei Wang, Yuehua Cheng +1
With the identity information in face data more closely related to personal credit and property security, people pay increasing attention to the protection of face data privacy. In…
Analyzing Adversarial Robustness of Deep Neural Networks in Pixel Space: a Semantic Perspective
Lina Wang, Xingshu Chen, Yulong Wang +4
The vulnerability of deep neural networks to adversarial examples, which are crafted maliciously by modifying the inputs with imperceptible perturbations to misled the network prod…
DFGC 2021: A DeepFake Game Competition
Bo Peng, Hongxing Fan, Wei Wang +20
This paper presents a summary of the DFGC 2021 competition. DeepFake technology is developing fast, and realistic face-swaps are increasingly deceiving and hard to detect. At the s…
Transferable Sparse Adversarial Attack
Ziwen He, Wei Wang, Jing Dong +1
Deep neural networks have shown their vulnerability to adversarial attacks. In this paper, we focus on sparse adversarial attack based on the norm constraint, which can su…
Exploring Adversarial Fake Images on Face Manifold
Dongze Li, Wei Wang, Hongxing Fan +1
Images synthesized by powerful generative adversarial network (GAN) based methods have drawn moral and privacy concerns. Although image forensic models have reached great performan…
Ulixes: Facial Recognition Privacy with Adversarial Machine Learning
Thomas Cilloni, Wei Wang, Charles Walter +1
Facial recognition tools are becoming exceptionally accurate in identifying people from images. However, this comes at the cost of privacy for users of online services with photo m…
Improving adversarial robustness of deep neural networks by using semantic information
Lina Wang, Rui Tang, Yawei Yue +4
The vulnerability of deep neural networks (DNNs) to adversarial attack, which is an attack that can mislead state-of-the-art classifiers into making an incorrect classification wit…
A Graph-theoretic Model to Steganography on Social Networks
Hanzhou Wu, Wei Wang, Jing Dong +2
Steganography aims to conceal the very fact that the communication takes place, by embedding a message into a digit object such as image without introducing noticeable artifacts. A…