20 citations · 179 across the 97 of their papers we have counts for
8 papers · 1 filter
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…
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…
Fast Local Attack: Generating Local Adversarial Examples for Object Detectors
Quanyu Liao, Xin Wang, Bin Kong +4
The deep neural network is vulnerable to adversarial examples. Adding imperceptible adversarial perturbations to images is enough to make them fail. Most existing research focuses…
Exposing GAN-generated Faces Using Inconsistent Corneal Specular Highlights
Shu Hu, Yuezun Li, Siwei Lyu
Sophisticated generative adversary network (GAN) models are now able to synthesize highly realistic human faces that are difficult to discern from real ones visually. In this work,…
Learning by Minimizing the Sum of Ranked Range
Shu Hu, Yiming Ying, Xin Wang +1
In forming learning objectives, one oftentimes needs to aggregate a set of individual values to a single output. Such cases occur in the aggregate loss, which combines individual l…
MagGAN: High-Resolution Face Attribute Editing with Mask-Guided Generative Adversarial Network
Yi Wei, Zhe Gan, Wenbo Li +5
We present Mask-guided Generative Adversarial Network (MagGAN) for high-resolution face attribute editing, in which semantic facial masks from a pre-trained face parser are used to…