Programmer trains artificial intelligence to draw faces from text descriptions

Programmer Animesh Karnewar wanted to know how characters described in books would appear in reality, so he turned to artificial intelligence to see if it could properly render these fictional people. Called T2F, the research project uses a generative adversarial network (GAN) to encode text and synthesize facial images. Simply put, a GAN consists of two neural networks that argue with each other to produce the best results. For example, the job of network No. 1 is to fool network No. 2 into believing a rendered image is a real photograph while network No. 2 sets out to prove the alleged photo is just a rendered image. This back-and-forth process fine-tunes the rendering process until network No. 2 is eventually fooled.