3 papers
cs.CV2024
Real-world Adversarial Defense against Patch Attacks based on Diffusion Model
Xingxing Wei, Caixin Kang, Yinpeng Dong +4
Adversarial patches present significant challenges to the robustness of deep learning models, making the development of effective defenses become critical for real-world applicatio…
cs.CV2024
DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks
Caixin Kang, Yinpeng Dong, Zhengyi Wang +4
Adversarial attacks, particularly patch attacks, pose significant threats to the robustness and reliability of deep learning models. Developing reliable defenses against patch atta…
cs.CV2024
Robust Classification via a Single Diffusion Model
Huanran Chen, Yinpeng Dong, Zhengyi Wang +4
Diffusion models have been applied to improve adversarial robustness of image classifiers by purifying the adversarial noises or generating realistic data for adversarial training.…