Using SRGANs to Generate Photo-Realistic Images

Super-Resolution Generative Adversarial Network, or SRGAN, is a Generative Adversarial Network (GAN) that can generate super-resolution images from low-resolution images, with finer details and higher quality. CNNs were earlier used to produce high-resolution images that train quicker and achieve high-level accuracy. However, in some cases, they are incapable of recovering finer details and often generate blurry images. In this chapter, we will implement an SRGAN network in the Keras framework that will be capable of generating high-resolution images. SRGANs were introduced in the paper titled, Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network, by Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, and others, which is available at the following link: https://arxiv.org...