OLANET: Self-Supervised 360° Depth Estimation with Effective Distortion-Aware View Synthesis and L1 Smooth Regularization

The distortion introduced by different projection (e.g. ERP, CUBE, etc) pose a great challenge to the depth estimation task of 360° images. We propose a novel approach, named OlaNet, to solve the self-supervised 360° depth estimation problem. Our method is motivated by two aspects: 1) the content of 360° imagery can be better learned by effective fields-of-views technology, i.e., atrous spatial py...