Neighbor combination and transformation for hallucinating faces

In this paper, we propose a novel face hallucination framework based on image patches, which exploits local geometry structures of overlapping patches to hallucinate different components associated with one facial image. To achieve local fidelity while preserving smoothness in the target highresolution image, we develop a neighbor combination superresolution model for high-resolution patch synthesis. For further enhancing the detailed information, we propose another model, which effectively learns neighbor transformations between low- and high-resolution image patch residuals to compensate modeling errors caused by the first model. Experiments demonstrate that our approach can hallucinate high quality super-resolution faces.

• Type: Conference
• Year: 2005
• Where: ICMCS
• Authors: Wei Liu, Dahua Lin, Xiaoou Tang
• Keywords: Face Hallucination Framework, ICMCS 2005, Image Patches, Neighbor Combination Superresolution