Learning to hallucinate face images via component generation and enhancement

• Main Authors: SONG, Yibing, ZHANG, Jiawei, HE, Shengfeng, BAO, Linchao, YANG, Qingxiong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Artificial intelligence; Tunneling (excavation); Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8429; https://ink.library.smu.edu.sg/context/sis_research/article/9432/viewcontent/0633.pdf
• Institution: Singapore Management University

We propose a two-stage method for face hallucination. First, we generate facial components of the input image using CNNs. These components represent the basic facial structures. Second, we synthesize fine-grained facial structures from high resolution training images. The details of these structures...