UCLA

Visual illusions have always been a highly popular topic among the general public. People enjoy the experience of having their eyes deceived by those fascinating visual arts. Mean- while, in the computer vision community, the recent boom in deep neural networks has proven to be a powerful tool for various vision tasks, ranging from image classification and depth estimation to three-dimensional scene reconstruction. If the ultimate goal for a neural network is to perceive scenes and objects as humans do, we can’t help but wonder: can neural networks also be tricked by visual illusions? In this work, we explore how Zero-1-to-3, a 3D scene reconstruction model, can be deceived by a special category of visual illusions: shading illusions.