GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians
About
We introduce GaussianAvatars, a new method to create photorealistic head avatars that are fully controllable in terms of expression, pose, and viewpoint. The core idea is a dynamic 3D representation based on 3D Gaussian splats that are rigged to a parametric morphable face model. This combination facilitates photorealistic rendering while allowing for precise animation control via the underlying parametric model, e.g., through expression transfer from a driving sequence or by manually changing the morphable model parameters. We parameterize each splat by a local coordinate frame of a triangle and optimize for explicit displacement offset to obtain a more accurate geometric representation. During avatar reconstruction, we jointly optimize for the morphable model parameters and Gaussian splat parameters in an end-to-end fashion. We demonstrate the animation capabilities of our photorealistic avatar in several challenging scenarios. For instance, we show reenactments from a driving video, where our method outperforms existing works by a significant margin.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Novel Expression Synthesis | NeRSemble | PSNR34.94 | 30 | |
| Head Avatar Reconstruction | INSTA dataset (test) | PSNR (bala)31.58 | 8 | |
| Head Avatar Reconstruction | GaussianBlendShapes (test) | PSNR (Subject 1)32.1 | 8 | |
| Novel View Synthesis | NeRSemble (test) | PSNR27.54 | 6 | |
| Head Avatar Reconstruction and Rendering | Head Avatar Reconstruction | Training Time (min)14 | 6 | |
| Monocular Facial Avatar Reconstruction | Overall Combined Datasets (test) | PSNR26.2 | 6 | |
| Monocular Facial Avatar Reconstruction | PointAvatar Dataset (test) | PSNR24.51 | 6 | |
| Monocular Facial Avatar Reconstruction | NerFace Dataset (test) | PSNR29.06 | 6 | |
| Monocular Facial Avatar Reconstruction | Ours Dataset (test) | PSNR24.18 | 6 | |
| 3D Talking Head Super-Resolution | FFHQ (test) | CSIM0.922 | 5 |