In this review article series, we will focus on a plethora of GANs for computer vision applications. Specifically, we will slowly build upon the ideas and the principles that led to the evolution of generative adversarial networks (GAN). We will encounter different tasks such as conditional image generation, 3D object generation, video synthesis.
The previous post was more or less introductory in GANs, generative learning, and computer vision. We reached the point of generating distinguishable image features in 128x128 images. In this part, we will continue our GAN journey in computer vision diving in more complex designs and better visual results. We will see mode collapse, 3D object generation, single RGB image to 3D object generation, and improved quality image to image mappings.