用于头部头像动画的3D高斯混合形状
3D Gaussian Blendshapes for Head Avatar Animation
AI总结：
本文提出3D高斯混合形状表示，从单目视频学习中性头部模型与表情混合形状，通过线性混合高斯实现任意表情建模，并利用高斯泼溅实时合成高保真头部头像动画，在细节捕捉和渲染性能上优于现有方法。
摘要：
我们引入3D高斯混合形状来建模逼真的头部头像。以单目视频为输入，我们学习一个中性表情的基础头部模型，以及一组表情混合形状，每个混合形状对应经典参数化人脸模型中的一个基础表情。中性模型和表情混合形状均表示为3D高斯，其中包含若干属性以描绘头像外观。任意表情的头像模型可以通过使用表情系数对高斯进行线性混合，将中性模型与表情混合形状有效结合而生成。高保真头部头像动画可以使用高斯泼溅实时合成。与最先进的方法相比，我们的高斯混合形状表示更好地捕捉了输入视频中展现的高频细节，并实现了更优的渲染性能。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
