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cs.CV2023
Model Inversion Attack via Dynamic Memory Learning
Gege Qi, YueFeng Chen, Xiaofeng Mao +4
Model Inversion (MI) attacks aim to recover the private training data from the target model, which has raised security concerns about the deployment of DNNs in practice. Recent adv…
cs.CV2023
ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing
Xiaodan Li, Yuefeng Chen, Yao Zhu +3
Recent studies have shown that higher accuracy on ImageNet usually leads to better robustness against different corruptions. Therefore, in this paper, instead of following the trad…
cs.CV2023
Information-containing Adversarial Perturbation for Combating Facial Manipulation Systems
Yao Zhu, Yuefeng Chen, Xiaodan Li +4
With the development of deep learning technology, the facial manipulation system has become powerful and easy to use. Such systems can modify the attributes of the given facial ima…