  We propose a new type of full-body human avatars, which combines parametric
mesh-based body model with a neural texture. We show that with the help of
neural textures, such avatars can successfully model clothing and hair, which
usually poses a problem for mesh-based approaches. We also show how these
avatars can be created from multiple frames of a video using backpropagation.
We then propose a generative model for such avatars that can be trained from
datasets of images and videos of people. The generative model allows us to
sample random avatars as well as to create dressed avatars of people from one
or few images. The code for the project is available at
saic-violet.github.io/style-people.
