@inproceedings{hu2020improved,
author = {Hu, Edward J. and Swaminathan, Adith and Salman, Hadi and Yang, Greg},
title = {Improved Image Wasserstein Attacks and Defenses},
booktitle = {2020 International Conference on Learning Representations},
year = {2020},
month = {July},
abstract = {Robustness against image perturbations bounded by a ℓp ball have been well-studied in recent literature. Perturbations in the real-world, however, rarely exhibit the pixel independence that ℓp threat models assume. A recently proposed Wasserstein distance-bounded threat model is a promising alternative that limits the perturbation to pixel mass movements. We point out and rectify flaws in previous definition of the Wasserstein threat model and explore stronger attacks and defenses under our better-defined framework. Lastly, we discuss the inability of current Wasserstein-robust models in defending against perturbations seen in the real world. Our code and trained models are available on GitHub.},
url = {http://approjects.co.za/?big=en-us/research/publication/improved-image-wasserstein-attacks-and-defenses/},
}