Automatic Depth Estimation and Background Blurring of Animated Scenes Based on Deep Learning

Abstract

Animation technology enables more accurate depth estimation and background blurring of animated scenes as it can enhance the sense of reality of the vision and increase its depth, thus it has become a hot spot in relevant research and production these days. However, although deep learning has made significant progresses in many research fields, its application in depth estimation and background blurring of animated scenes is still facing a few challenges. Most available technologies are for real world images, not animations, so there are certain difficulties capturing the unique styles of animations and their details. This study proposes two technical schemes specifically designed for animated scenes: a depth estimation model based on DenseNet, and a deblurring algorithm based on Very Deep Super Resolution (VDSR), in the hopes of providing solutions for the above mentioned matters, as well as forging more efficient and accurate tools for the animation industry.