We train a synthetic prior model to capture the distribution of human heads with arbitrary facial expressions. The prior model is a conditional NeRF with three additional inputs modeling the identity, the expression, out-of-3DMM properties like hair, clothing, and appearance.

We show training set reconstructions and interpolations for each of the latent spaces below.