3D Gaussian Blendshapes for Head Avatar Animation
This work addresses the problem of creating realistic head avatars for applications like virtual reality or gaming, but it appears incremental as it builds on existing blendshape and Gaussian representation techniques.
The authors tackled the problem of modeling photorealistic head avatars from monocular video by introducing 3D Gaussian blendshapes, achieving real-time animation with superior rendering performance and better capture of high-frequency details compared to state-of-the-art methods.
We introduce 3D Gaussian blendshapes for modeling photorealistic head avatars. Taking a monocular video as input, we learn a base head model of neutral expression, along with a group of expression blendshapes, each of which corresponds to a basis expression in classical parametric face models. Both the neutral model and expression blendshapes are represented as 3D Gaussians, which contain a few properties to depict the avatar appearance. The avatar model of an arbitrary expression can be effectively generated by combining the neutral model and expression blendshapes through linear blending of Gaussians with the expression coefficients. High-fidelity head avatar animations can be synthesized in real time using Gaussian splatting. Compared to state-of-the-art methods, our Gaussian blendshape representation better captures high-frequency details exhibited in input video, and achieves superior rendering performance.