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

This paper introduces SRGAN, a deep learning model that uses a generative adversarial network (GAN) to enhance the resolution of images. It focuses on creating realistic and detailed high-resolution images from low-resolution inputs, moving beyond traditional methods that often produce blurry results. The model combines perceptual loss functions with adversarial training to generate images that are not only of higher resolution but also visually more appealing and realistic.