Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

This paper introduces SRGAN, a generative adversarial network (GAN) for enhancing the resolution of images. It aims to create more realistic and detailed high-resolution images from low-resolution inputs by using a network trained to fool a discriminator, leading to sharper and more visually appealing results compared to traditional methods that often produce blurry images.