View Interpolation Networks for Reproducing Material Appearance of Specular Objects

Abstract

In this study, we propose view interpolation networks to reproduce changes in the brightness of an object's surface depending on the viewing direction, which is important in reproducing the material appearance of a real object. We use an original and a modified version of U-Net for image transformation. The networks were trained to generate images from intermediate viewpoints of four cameras placed at the corners of a square. We conducted an experiment with three different combinations of methods and training data formats. We found that it is best to input the coordinates of the viewpoints together with the four camera images and to use images from random viewpoints as the training data.