Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos

Figure 1 . Our technique builds a 3D avatar representation of a person using just a single short monocular RGB video (e.g., 1-2 minutes). We leverage a 3DMM to track the user's expressions. By anchoring a neural radiance field to the 3DMM geometry, we generate a volumetric photorealistic 3D avatar that can be rendered with user-defined expression and viewpoint. Note that our method works well on challenging materials, e.g., hair and dramatic expressions. Please see our webpage augmentedperception.github.io/monoavatar for more results.