GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification

27 May 2019

Papers citing "GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification"

8 / 8 papers shown

Title
All You Need is RAW: Defending Against Adversarial Attacks with Camera Image Pipelines Yuxuan Zhang B. Dong Felix Heide AAML 26 8 0 16 Dec 2021
Medical Aegis: Robust adversarial protectors for medical images Qingsong Yao Zecheng He S. Kevin Zhou AAML MedIm 30 2 0 22 Nov 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 30 65 0 24 Jul 2021
Salient Feature Extractor for Adversarial Defense on Deep Neural Networks Jinyin Chen Ruoxi Chen Haibin Zheng Zhaoyan Ming Wenrong Jiang Chen Cui AAML 25 10 0 14 May 2021
Learning Energy-Based Models With Adversarial Training Xuwang Yin Shiying Li Gustavo K. Rohde AAML DiffM 33 9 0 11 Dec 2020
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,112 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,842 0 08 Jul 2016