Abstract
We introduce GaussianAvatars1, 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.
Original language | English |
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Pages (from-to) | 20299-20309 |
Number of pages | 11 |
Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
DOIs | |
State | Published - 2024 |
Event | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024 - Seattle, United States Duration: 16 Jun 2024 → 22 Jun 2024 |
Keywords
- Gaussian Splatting
- Human Head Avatar
- Video Synthesis