Personalized 3D avatars require an animatable representation of digital humans. Doing so instantly from monocular videos offers scalability to broad class of users and wide-scale applications. In this paper, we present a fast, simple, yet effective method for creating animatable 3D digital humans from monocular videos. Our method utilizes the efficiency of Gaussian splatting to model both 3D geometry and appearance. However, we observed that naively optimizing Gaussian splats results in inaccurate geometry, thereby leading to poor animations. This work achieves and illustrates the need of accurate 3D mesh-type modelling of the human body for animatable digitization through Gaussian splats. This is achieved by developing a novel pipeline that benefits from three key aspects: (a) implicit modelling of surface's displacements and the color's spherical harmonics; (b) binding of 3D Gaussians to the respective triangular faces of the body template; (c) a novel technique to render normals followed by their auxiliary supervision. Our exhaustive experiments on three different benchmark datasets demonstrates the state-of-the-art results of our method, in limited time settings. In fact, our method is faster by an order of magnitude (in terms of training time) than its closest competitor. At the same time, we achieve superior rendering and 3D reconstruction performance under the change of poses.
个性化3D头像需要一种可动画化的数字人类表现形式。通过单目视频即时实现这一点，可以扩展到广泛的用户和大规模应用。在本文中，我们介绍了一种快速、简单且有效的方法，用于从单目视频创建可动画化的3D数字人类。我们的方法利用高斯喷溅的效率来同时建模3D几何形状和外观。然而，我们观察到，简单地优化高斯喷溅会导致几何形状不准确，从而导致动画效果差。本工作通过高斯喷溅实现并展示了精确的3D网格类型人体建模对可动画数字化的需求。这是通过开发一个从三个关键方面受益的新颖流程实现的：(a) 表面位移和颜色球谐的隐式建模；(b) 将3D高斯绑定到身体模板的相应三角形面；(c) 一种渲染法线的新技术，随后进行辅助监督。我们在三个不同的基准数据集上进行的详尽实验展示了我们方法在有限时间设置中的最新成果。事实上，就训练时间而言，我们的方法比最接近的竞争者快一个数量级。同时，在姿势变化下，我们实现了更优越的渲染和3D重建性能。