What is: SRGAN?
|Source||Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network|
|Data Source||CC BY-SA - https://paperswithcode.com|
SRGAN is a generative adversarial network for single image super-resolution. It uses a perceptual loss function which consists of an adversarial loss and a content loss. The adversarial loss pushes the solution to the natural image manifold using a discriminator network that is trained to differentiate between the super-resolved images and original photo-realistic images. In addition, the authors use a content loss motivated by perceptual similarity instead of similarity in pixel space. The actual networks - depicted in the Figure to the right - consist mainly of residual blocks for feature extraction.
Formally we write the perceptual loss function as a weighted sum of a (VGG) content loss and an adversarial loss component :