可重光照、可驱动的高斯化身的交互式渲染
Interactive Rendering of Relightable and Animatable Gaussian Avatars
AI总结：
针对数字人创建中可重光照可驱动化身的渲染效率问题，提出基于高斯溅射的高效方法，解耦材质与光照，实现新视角姿态光照下的交互式高质量渲染，速度和效果优于现有方法。
摘要：
从多视角或单目视频中创建可重光照、可驱动的化身，是数字人创作与虚拟现实应用中的一项挑战性任务。以往方法依赖神经辐射场或光线追踪，导致训练和渲染过程缓慢。我们利用高斯溅射（Gaussian Splatting）技术，提出了一种简单高效的方法，从稀疏视角或单目化身视频中解耦人体材质与光照，使化身能够在新视角、新姿态和新光照下以交互帧率（6.9 fps）同时渲染。具体而言，我们首先通过有符号距离函数获取标准人体网格，并为每个网格顶点分配属性。随后，标准空间中的高斯从邻近的人体网格顶点插值得到属性。接着我们通过前向蒙皮将高斯变形到姿态空间，并将可学习的环境光与高斯属性结合进行着色计算。为实现快速阴影建模，我们从密集视角对姿态下的人体网格进行光栅化以获取可见性。我们的方法不仅简单，而且速度足够快，能够在环境光变化下实现化身动画的交互式渲染。实验表明，与以往工作相比，我们的方法在合成数据集和真实数据集上都能以更快的速度渲染出质量更高的结果。
英文摘要：
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.
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。
