2 citations · 5 across the 4 of their papers we have counts for
4 papers
StealthDiffusion: Towards Evading Diffusion Forensic Detection through Diffusion Model
Ziyin Zhou, Ke Sun, Zhongxi Chen +3
The rapid progress in generative models has given rise to the critical task of AI-Generated Content Stealth (AIGC-S), which aims to create AI-generated images that can evade both f…
DLIP: Distilling Language-Image Pre-training
Huafeng Kuang, Jie Wu, Xiawu Zheng +5
Vision-Language Pre-training (VLP) shows remarkable progress with the assistance of extremely heavy parameters, which challenges deployment in real applications. Knowledge distilla…
Latent Feature Relation Consistency for Adversarial Robustness
Xingbin Liu, Huafeng Kuang, Hong Liu +3
Deep neural networks have been applied in many computer vision tasks and achieved state-of-the-art performance. However, misclassification will occur when DNN predicts adversarial…
CAT:Collaborative Adversarial Training
Xingbin Liu, Huafeng Kuang, Xianming Lin +2
Adversarial training can improve the robustness of neural networks. Previous methods focus on a single adversarial training strategy and do not consider the model property trained…