We've seen a lot of research lately that uses neural networks to upsample low resolution images and the results have been impressive – even a little creepy. Google recently showcased a system that can turn a low resolution 8x8 input image into a 32x32 sample that's remarkably close to the original image.

Inspired by recent breakthroughs, research engineer Roland Meertens found another application for neural networks – one that's highly relevant to our interests. He created an application that turns low-res, monochrome Game Boy Camera images into photorealistic color images.

Original images in the center, Game Boy-ified images on the left and image generated by neural network on the right

A network must be trained, and training means feeding it input images. To create a training data set, Meertens gave some 'real life images' a Game Boy Camera treatment by re-creating them in four shades of black. By comparing the Game Boy-ified images with the originals, the network is 'taught' how to convert the images to color. With the network trained and ready, Meertens began testing it on celebrity photos as well as images from the Game Boy Camera (including the game's mysterious character at the top of the page).

Finally, Meertens uses the application on an image taken with the Game Boy Camera. Naturally, it should be a selfie, as it is here. If you have all of the necessary components, taking a photo with the Game Boy camera is easy. Getting it onto your computer is another story. Lacking a specialized cable, Meertens did his best to photograph the Game Boy screen. As a result the lighting is slightly uneven, which affects the output from the network, but the re-creation is still pretty darn cool. Our hats are off to him.

2017-2-21 12:00