Artist and researcher Branislav Ulicny (“AlteredQualia”) developed an online demo that combines two different deep learning-based projects into spooky cursor-tracking faces.
The first is a hobby project by Mike Tyka, who works on machine learning at Google, makes use of GANs to generate realistic new faces. Using a TITAN X GPU, Tyke trained his generative model on nearly 20,000 which were then used as the base for the portraits.
“It uses a technique called “generative adversarial networks” (“GAN”) where two artificial neural networks are playing an adversarial game: one (the “Generator”) tries to generate increasingly convincing output, while a the second (the “Critic”) tries to learn to distinguish real photos from generated ones. With time, the generated output becomes increasingly realistic, as both adversaries try to outwit each other,” Tyka told Mashable.
DeepWarp developed by computer vision researchers at the Skolkovo Institute of Science and Technology (Skoltech) in Russia, is used to move the eyeballs in the portraits. The realistic gaze manipulation software was trained using a TITAN X GPU and the cuDNN-accelerated Torch deep learning framework, and when combined with Tyka’s project, it produces some haunted-looking paintings.

The interactive “eyes gaze warping” online demo features 13 different characters.
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AI-Generated Summary
- Artist and researcher Branislav Ulicny created an interactive online demo that combines two deep learning projects into cursor-tracking faces.
- Mike Tyka trained a generative adversarial network on nearly 20,000 faces using a TITAN X GPU to produce realistic base portraits.
- Researchers at the Skolkovo Institute of Science and Technology developed DeepWarp, gaze manipulation software trained with a TITAN X GPU and the cuDNN-accelerated Torch framework, to animate the eyes in the portraits.
Next Steps
- Read the Popular Mechanics article for additional details on the project.
- Explore the interactive online demo to experience the cursor-tracking faces directly.
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