18 citations · 29 across the 8 of their papers we have counts for
12 papers
ShapeEditer: a StyleGAN Encoder for Face Swapping
Shuai Yang, Kai Qiao
In this paper, we propose a novel encoder, called ShapeEditor, for high-resolution, realistic and high-fidelity face exchange. First of all, in order to ensure sufficient clarity a…
Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout
Pengfei Xie, Linyuan Wang, Ruoxi Qin +4
Deep neural networks(DNNs) is vulnerable to be attacked by adversarial examples. Black-box attack is the most threatening attack. At present, black-box attack methods mainly adopt…
Defense-guided Transferable Adversarial Attacks
Zifei Zhang, Kai Qiao, Jian Chen +1
Though deep neural networks perform challenging tasks excellently, they are susceptible to adversarial examples, which mislead classifiers by applying human-imperceptible perturbat…
Neural encoding and interpretation for high-level visual cortices based on fMRI using image caption features
Kai Qiao, Chi Zhang, Jian Chen +3
On basis of functional magnetic resonance imaging (fMRI), researchers are devoted to designing visual encoding models to predict the neuron activity of human in response to present…
BigGAN-based Bayesian reconstruction of natural images from human brain activity
Kai Qiao, Jian Chen, Linyuan Wang +3
In the visual decoding domain, visually reconstructing presented images given the corresponding human brain activity monitored by functional magnetic resonance imaging (fMRI) is di…
AdvJND: Generating Adversarial Examples with Just Noticeable Difference
Zifei Zhang, Kai Qiao, Lingyun Jiang +2
Compared with traditional machine learning models, deep neural networks perform better, especially in image classification tasks. However, they are vulnerable to adversarial exampl…