Synthesizing high resolution photorealistic images has been a long-standing challenge in machine learning. In this project we use a new methods for the improved training of generative adversarial networks (GANs) for image synthesis. Construct a variant of GANs employing label conditioning that results in 128x128 resolution image samples exhibiting global coherence.
