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Short answer: Yes, Long answer: No! Indeed, research on adversarialrobustness has led to invaluable insights helping us understand and exploredifferent aspects of the problem. Many attacks and defenses have been proposedover the last couple of years. The problem, however, remains largely unsolvedand poorly understood. Here, I argue that the current formulation of theproblem serves short term goals, and needs to be revised for us to achievebigger gains. Specifically, the bound on perturbation has created a somewhatcontrived setting and needs to be relaxed. This has misled us to focus on modelclasses that are not expressive enough to begin with. Instead, inspired byhuman vision and the fact that we rely more on robust features such as shape,vertices, and foreground objects than non-robust features such as texture,efforts should be steered towards looking for significantly different classesof models. Maybe instead of narrowing down on imperceptible adversarialperturbations, we should attack a more general problem which is findingarchitectures that are simultaneously robust to perceptible perturbations,geometric transformations (e.g. rotation, scaling), image distortions(lighting, blur), and more (e.g. occlusion, shadow). Only then we may be ableto solve the problem of adversarial vulnerability.

Is current research on adversarial robustness addressing the right problem?