To make an age-altering AI tool that was ready for the demands of Hollywood and flexible enough to work on moving footage or shots where an actor isn’t always looking directly at the camera, Disney’s researchers, as detailed in a recently published paper, first created a database of thousands of randomly generated synthetic faces. Existing machine learning aging tools were then used to age and de-age these thousands of non-existent test subjects, and those results were then used to train a new neural network called FRAN (face re-aging network).
When FRAN is fed an input headshot, instead of generating an altered headshot, it predicts what parts of the face would be altered by age, such as the addition or removal of wrinkles, and those results are then layered over the original face as an extra channel of added visual information. This approach accurately preserves the performer’s appearance and identity, even when their head is moving, when their face is looking around, or when the lighting conditions in a shot change over time. It also allows the AI generated changes to be adjusted and tweaked by an artist, which is an important part of VFX work: making the alterations perfectly blend back into a shot so the changes are invisible to an audience.
