AI Lab: Learn to Code with the Cutting-Edge Microsoft AI Platform

The network consists of two machine learning models, one that generates images from text descriptions and another, known as a discriminator, that uses text descriptions to judge the authenticity of generated images. The generator attempts to get fake pictures past the discriminator; the discriminator never wants to be fooled. Working together, the discriminator pushes the generator toward perfection. As humans draw, we repeatedly refer to the text and pay close attention to the words that describe the region of the image we are drawing. To capture this human trait, the researchers created what they call an attentional GAN, or AttnGAN, that mathematically represents the human concept of attention.