Pix2Pix-GAN: paired style transfer
In Chapter 12, we discussed a number of innovations related to GAN architectures that led to improved results and better control of the output class. One of those innovations was conditional GANs. This simple yet powerful addition to the GAN setup enabled us to navigate the latent vector space and control the generator to generate specific outputs. We experimented with a simple MNIST conditional GAN where we were able to generate the output of our choice. In this section, we will cover a variant of conditional GANs in the context of style transfer. We will go through the details of the Pix2Pix architecture and its important components and also train a paired style transfer network of our own. We will close this section with some amazing and innovative use cases of such a capability.
In their work titled Image to Image Translation with Conditional Adversarial Networks4, Isola et al. present a conditional GAN network called pix2pix, which can learn...
