Share This Author
RobustBench: a standardized adversarial robustness benchmark
- Francesco Croce, Maksym Andriushchenko, Matthias Hein
- Computer ScienceNeurIPS Datasets and Benchmarks
- 19 October 2020
This work evaluates robustness of models for their benchmark with AutoAttack, an ensemble of white- and black-box attacks which was recently shown in a large-scale study to improve almost all robustness evaluations compared to the original publications.
Adversarially Robust Vision Transformers
A Light Recipe to Train Robust Vision Transformers
This paper shows that ViTs are highly suitable for adversarial training to achieve competitive performance and recommends that the community should avoid translating the canonical training recipes in ViTs to robust training and rethink common training choices in the context of adversarialTraining.