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.

翻译：我们提出GaussianAvatars，一种新型方法用于创建在表情、姿态和视角上完全可控的逼真头部化身。其核心思想是一种基于3D高斯散点的动态三维表示，该散点被绑定到参数化可变形人脸模型上。这种结合不仅实现了逼真的渲染效果，还通过底层参数模型（例如从驱动序列进行表情迁移或手动调整变形模型参数）实现了精确的动画控制。我们将每个高斯散点参数化为三角形的局部坐标框架，并优化显式位移偏移以获取更精确的几何表示。在化身重建过程中，我们以端到端方式联合优化变形模型参数与高斯散点参数。我们通过多个具有挑战性的场景展示了该逼真化身的动画能力，例如，在驱动视频的重演任务中，我们的方法以显著优势超越了现有工作。