Overview of Important GAN Models & Applications

Author(s): Youssef Hosni

Originally published on Towards AI.

Generative adversarial networks (GANs) have revolutionized image synthesis since their introduction in 2014. This article provides an overview of some of the most influential GAN models for key computer vision applications, such as text-to-image generation, image-to-image translation, and image super-resolution.

GANs work by training two neural networks — a generator and a discriminator — in an adversarial game to output synthetic images that are indistinguishable from real images.

The first section describes StackGAN, a pioneering text-to-image GAN that uses a two-stage process to generate high-resolution, photo-realistic images from text descriptions.

Next, Pix2Pix GANs are examined for the general task of image-to-image translation across… Read the full blog for free on Medium.

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Published via Towards AI