23 citations · 61 across the 5 of their papers we have counts for
6 papers
Self-supervised Transformer for Deepfake Detection
Hanqing Zhao, Wenbo Zhou, Dongdong Chen +2
The fast evolution and widespread of deepfake techniques in real-world scenarios require stronger generalization abilities of face forgery detectors. Some works capture the feature…
Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain
Honggu Liu, Xiaodan Li, Wenbo Zhou +5
The remarkable success in face forgery techniques has received considerable attention in computer vision due to security concerns. We observe that up-sampling is a necessary step o…
Multi-attentional Deepfake Detection
Hanqing Zhao, Wenbo Zhou, Dongdong Chen +3
Face forgery by deepfake is widely spread over the internet and has raised severe societal concerns. Recently, how to detect such forgery contents has become a hot research topic a…
Improved Image Matting via Real-time User Clicks and Uncertainty Estimation
Tianyi Wei, Dongdong Chen, Wenbo Zhou +4
Image matting is a fundamental and challenging problem in computer vision and graphics. Most existing matting methods leverage a user-supplied trimap as an auxiliary input to produ…
Model Watermarking for Image Processing Networks
Jie Zhang, Dongdong Chen, Jing Liao +5
Deep learning has achieved tremendous success in numerous industrial applications. As training a good model often needs massive high-quality data and computation resources, the lea…
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…