High-quality face image generated with conditional boundary equilibrium generative adversarial networks

• Main Authors: Huang, Bin, Chen, Weihai, Wu, Xingming, Lin, Chun-Liang, Suganthan, Ponnuthurai Nagaratnam
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Super Resolution; Generative Adversarial Network
• Online Access: https://hdl.handle.net/10356/142052
• Institution: Nanyang Technological University

We propose a novel single face image super-resolution method, which is named Face Conditional Generative Adversarial Network (FCGAN), based on boundary equilibrium generative adversarial networks. Without taking any prior facial information, our approach combines the pixel-wise L1 loss and GAN loss...