Be Your Own Neighborhood: Detecting Adversarial Example by the
Neighborhood Relations Built on Self-Supervised Learning

Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning

31 August 2022

Tsung-Yi Ho

Papers citing "Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning"

4 / 4 papers shown

Title
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses Francesco Croce Sven Gowal T. Brunner Evan Shelhamer Matthias Hein A. Cemgil TTA AAML 173 67 0 28 Feb 2022
What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction Yijun Yang Ruiyuan Gao Yu Li Qiuxia Lai Qiang Xu GAN AAML 29 20 0 24 Jan 2022
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 217 674 0 19 Oct 2020
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 50 101 0 16 Oct 2019