What is it about?
Face super-resolution is to convert low-resolution blurred face images into clear and high-resolution face output. At present, the advanced method is to use GAN ways to do face super-resolution. Here, from the earliest GAN model, UR-DGN, to the latest model, FSRCH, we review the development process of taking GAN as a deep model for face super-resolution in the last two years.
Photo by Aleksandr Kozlovskii on Unsplash
Why is it important?
Our findings show that the face super-resolution technology based on GAN is developing towards the direction of preserving the face detailed features of large scale (over 8 times) up-sampling.
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This page is a summary of: A Survey on GAN-based Face Hallucination with Its Model Development, IET Image Processing, February 2019, the Institution of Engineering and Technology (the IET),
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