Accurate Monocular Depth Estimation on Water Scenes via Self-supervised Learning of Specular Reflection Priors

The core message of this article is that the authors propose a self-supervised monocular depth estimation framework that leverages specular reflection priors in water scenes to reformulate the ill-posed depth estimation task as an interpretable multi-view synthesis problem.