I have been lowkey obsessed with snapchat for a while now and decided to scrape some images from instagram to see what a neural network made of them. I expected the Generative Adversarial Network to meld together the Augmented Reality components with the faces to create something nightmarish. What I didn’t expect was the GAN to detect the commonality in the images and erase the components all together!

Generative Adversarial Network grid at mode collapse

Working first with a DCGAN I trained until it reached mode collapse. I really enjoy watching neural networks collapse and the converging grids made for some really interesting works. While training I also used the face picker in snapchat to see if it would recognize any of the faces and was shocked when it separated them all out and used them all, with horrifying and hilarious results! I documented this progress on Twitter in a lengthy thread as I explored everything snapchat.

A grid of four generated faces that have been style transferred. They look like they are melting.

From there I used style transfer to upsample my images and create compelling works for the art that will be on display. When the exhibition goes live I will publish the art and snapcodes on my website so that everyone can join in the fun even remotely!

A pair of people wearing generated faces over their own. They look surprised.

If you have fun with this project please share it around and if you use the lenses tag me in or use #snapchatgan so I can see your wonderful works!

A hand taking a selfie holding up a phone to a generated face. The face has been style transferred to look like a painting. The face taking the selfie is wearing the work as a mask.