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.
我们介绍了GaussianAvatars，这是一种创建逼真的头部虚拟化形象的新方法，这些形象在表情、姿势和视点方面都是完全可控的。核心思想是基于3D高斯喷溅的动态3D表示，这些喷溅被绑定到一个参数化的可变形面部模型。这种组合促进了逼真的渲染，同时允许通过底层参数模型进行精确的动画控制，例如，通过从驱动序列传递表情或手动更改可变形模型参数。我们通过三角形的局部坐标框架参数化每个喷溅，并优化显式位移偏移，以获得更准确的几何表示。在虚拟化形象重建过程中，我们以端到端的方式联合优化可变形模型参数和高斯喷溅参数。我们在几个具有挑战性的场景中展示了我们逼真虚拟化形象的动画能力。例如，我们展示了从驱动视频中的再现，其中我们的方法在性能上显著超越了现有工作。