Degraded Polygons Raise Fundamental Questions of Neural Network Perception

It is well-known that modern computer vision systems often exhibit behaviors misaligned with those of humans: from adversarial attacks to image corruptions, deeplearning vision models suffer in a variety of settings that humans capably handle. Inlight of these phenomena, here we introduce another, orthogonal perspective studying the human-machine vision gap.