Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser

CVPR 2018 Fangzhou LiaoMing LiangYinpeng DongTianyu PangXiaolin HuJun Zhu

Neural networks are vulnerable to adversarial examples, which poses a threat to their application in security sensitive systems. We propose high-level representation guided denoiser (HGD) as a defense for image classification... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet