MarioNETte: Few-Shot Identity Preservation in Facial Reenactment

If you've ever wanted to see Einstein play charades, Rodin's "The Thinker" wink at you, or an ancient Chinese Emperor cast in a Chaplin movie -- then the AI-powered video transformation tech you're looking for is "face reenactment," which can digitally deliver all such fantastic scenarios. Unlike face swapping, which transfers a face from one source to another, face reenactment captures the movements of a driver face and expresses them through the identity of a target face. Starting with a dynamic driver face, researchers can manipulate any target face -- from today's celebrities to historical figures, including any age, ethnicity or gender -- to perform any humanly possible face-based task. Previous approaches at synthesizing a reenacted face used generative adversarial networks (GAN), which have demonstrated tremendous ability is a wide range of image generation tasks. GAN-based models however require at least a few minutes of training data for each target.