MIT researchers developed an algorithm trained to generate horrifying images in an attempt to find the scariest faces and locations possible, and then rely on humans to see which approach makes the freakiest images.
Using TITAN X GPUs and cuDNN to train their deep learning models, the researchers used the infamous style transfer technique and generative adversarial networks to curate the ghoulish images.
“We use state-of-the-art deep learning algorithms to learn what haunted houses, ghost towns or toxic cities look like,” said MIT Media Lab researcher Pinar Yanardag Delul.
The algorithm extracts elements — such as a bruised-black palette — from scary templates and implants them in the landmarks.
The researchers also used Google’s DeepDream to develop ghastly portraits and voters can rate the images on the Nightmare Machine website to teach the system to make images even scarier.
