Creating relightable and animatable avatars from multi-view or monocular videos is a challenging task for digital human creation and virtual reality applications. Previous methods rely on neural radiance fields or ray tracing, resulting in slow training and rendering processes. By utilizing Gaussian Splatting, we propose a simple and efficient method to decouple body materials and lighting from sparse-view or monocular avatar videos, so that the avatar can be rendered simultaneously under novel viewpoints, poses, and lightings at interactive frame rates (6.9 fps). Specifically, we first obtain the canonical body mesh using a signed distance function and assign attributes to each mesh vertex. The Gaussians in the canonical space then interpolate from nearby body mesh vertices to obtain the attributes. We subsequently deform the Gaussians to the posed space using forward skinning, and combine the learnable environment light with the Gaussian attributes for shading computation. To achieve fast shadow modeling, we rasterize the posed body mesh from dense viewpoints to obtain the visibility. Our approach is not only simple but also fast enough to allow interactive rendering of avatar animation under environmental light changes. Experiments demonstrate that, compared to previous works, our method can render higher quality results at a faster speed on both synthetic and real datasets.

翻译：从多视角或单目视频中创建可重光照与可动画的化身，是数字人创作和虚拟现实应用中的一项挑战性任务。先前的方法依赖于神经辐射场或光线追踪，导致训练和渲染过程缓慢。通过利用高斯泼溅技术，我们提出了一种简单高效的方法，能够从稀疏视角或单目化身视频中解耦身体材质与光照，从而使得化身能够以交互式帧率（6.9 fps）在新颖的视角、姿态和光照条件下同时进行渲染。具体而言，我们首先使用有符号距离函数获取规范身体网格，并为每个网格顶点分配属性。随后，规范空间中的高斯点通过插值附近身体网格顶点的属性来获取其自身属性。我们接着使用前向蒙皮技术将高斯点变形到姿态空间，并将可学习的环境光与高斯属性相结合以进行着色计算。为了实现快速的阴影建模，我们从密集的视角对姿态身体网格进行光栅化以获取可见性信息。我们的方法不仅简单，而且速度足够快，能够实现环境光变化下化身动画的交互式渲染。实验表明，与先前工作相比，我们的方法在合成数据集和真实数据集上均能以更快的速度渲染出更高质量的结果。