In this article I will show how to use artificial intelligence to generate human faces.
Before you will continue reading please watch short introduction:
Generative adversarial network
To generate realistic human faces, we can use neural networks with GAN (Generative adversarial network) architecture.
The GaN network consists of two parts of the Generator whose task is to generate the image from random input and a discriminator that checks if the generated image is realistic.
During training, the networks compete with each other, the generator tries to generate better and better images
and thereby deceive the Discriminator. On the other hand, the Discriminator learns to distinguish between real and generated photos.
To train the discriminator, we use both real photos and those generated by the generator.
Finally, we can achieve the following results using DCGAN network.
As you can see some faces look realistic while some are distorted, additionally the network can only generate low resolution images.
I generated the images using pretrained networks and the effect is really amazing.