activity
20182022
most citedHiding Faces in Plain Sight: Disrupting AI Face Synthesis with Adversarial Perturbations

22 citations · 57 across the 8 of their papers we have counts for

collaborators

17 papers

cs.CV2022

Enhancing the Transferability via Feature-Momentum Adversarial Attack

Xianglong, Yuezun Li, Haipeng Qu +1

Transferable adversarial attack has drawn increasing attention due to their practical threaten to real-world applications. In particular, the feature-level adversarial attack is on…

cs.CV202119 cited

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…

cs.CV2021

DeepFake-o-meter: An Open Platform for DeepFake Detection

Yuezun Li, Cong Zhang, Pu Sun +2

In recent years, the advent of deep learning-based techniques and the significant reduction in the cost of computation resulted in the feasibility of creating realistic videos of h…

cs.CV2021

Landmark Breaker: Obstructing DeepFake By Disturbing Landmark Extraction

Pu Sun, Yuezun Li, Honggang Qi +1

The recent development of Deep Neural Networks (DNN) has significantly increased the realism of AI-synthesized faces, with the most notable examples being the DeepFakes. The DeepFa…

cs.CR2020

Invisible Backdoor Attack with Sample-Specific Triggers

Yuezun Li, Yiming Li, Baoyuan Wu +3

Recently, backdoor attacks pose a new security threat to the training process of deep neural networks (DNNs). Attackers intend to inject hidden backdoors into DNNs, such that the a…

cs.CV20202 cited

LandmarkGAN: Synthesizing Faces from Landmarks

Pu Sun, Yuezun Li, Honggang Qi +1

Face synthesis is an important problem in computer vision with many applications. In this work, we describe a new method, namely LandmarkGAN, to synthesize faces based on facial la…