A Gentle Introduction to the Progressive Growing GAN

Progressive Growing GAN is an extension to the GAN training process that allows for the stable training of generator models that can output large high-quality images. It involves starting with a very small image and incrementally adding blocks of layers that increase the output size of the generator model and the input size of the discriminator model until the desired image size is achieved. This approach has proven effective at generating high-quality synthetic faces that are startlingly realistic. In this post, you will discover the progressive growing generative adversarial network for generating large images. Discover how to develop DCGANs, conditional GANs, Pix2Pix, CycleGANs, and more with Keras in my new GANs book, with 29 step-by-step tutorials and full source code.