1 Introduction
Many problems in computer vision can be cast as transforming images from one form to another. In this work, we assume that the pairs of images have the same content and are in registration with each other, but are visually different. Typical applications include, but are not limited to, super-resolution (SR), face mapping of different styles, estimation of intrinsic images, such as shading and albedo images, and various nonphotorealistic rendering. Some existing methods generate stylistic images based on a single or a pair of reference images [3], [1], [2]. Others learn the mapping relations from large training sets of paired images [4], [6], [7], [8], [49], [51]. Our work belongs to the second category. A few representative methods of such kind are summarized as follows.