Learning a Personalized Generative Prior for Face Images

摘要

Figure 1: Using our personalized prior forMichelle Obama, we solve inpainting, super-resolution, and semantic editing (smile), while faithfully preservingher key facial characteristic. Each example shows the original input image,whichmaybe corrupted (top left), and the output based on our personalized (right) and generic (bottom left) face priors. The generic face prior is learned from a diverse set of images and produces results that do not preserve Obama’s key facial characteristics. Left and middle blocks ©U.S. Government, right block ©Tim Pierce.