Draw the Desire: Bringing the sketches to life using Deep Learning

In this article, you will learn about conditional GAN (Generative Adversarial Network) and will be able to build one from scratch. After that you will be able to apply the cGAN model on a fashion products dataset for converting sketches of products to color images. If you would like to understand what are GANs [1] you can check out our previous tutorials on Latent Spaces.

Figure 1: An example output of the GAN network trained on Fashion Products