一种基于混合基元的 Gaussian Splatting 表面重建方法
A Mixed-Primitive-based Gaussian Splatting Method for Surface Reconstruction
AI总结：
针对现有 Gaussian Splatting 仅用单一基元表示复杂表面导致质量不足的问题，提出首个支持多种几何基元混合的表面重建框架，通过组合 splatting 策略、混合初始化与顶点剪枝机制，实现了高质量的表面重建。
摘要：
最近，Gaussian Splatting (GS) 在表面重建中受到了广泛关注。然而，尽管现实世界中的 3D 物体可能具有复杂且多样的形状，现有的基于 GS 的方法在重建过程中仅有限地使用单一类型的 splatting 基元（Gaussian ellipse 或 Gaussian ellipsoid）来表示物体表面。在本文中，我们强调这对于高质量地表示物体表面可能是不够的。因此，我们提出了一个新颖的框架，该框架首次使 Gaussian Splatting 能够在其表面重建过程中结合多种类型的（几何）基元。具体而言，在我们的框架中，我们首先提出了一种组合 splatting 策略，使得不同类型的基元能够在 Gaussian Splatting 流水线中被进行 splatting 和渲染。此外，我们还为我们的框架设计了基于混合基元的初始化策略和顶点剪枝机制，以进一步促进其利用不同类型基元良好地执行表面表示学习过程。大量实验证明了我们框架的有效性及其准确的表面重建性能。
英文摘要：
Recently, Gaussian Splatting (GS) has received a lot of attention in surface reconstruction. However, while 3D objects can be of complex and diverse shapes in the real world, existing GS-based methods only limitedly use a single type of splatting primitive (Gaussian ellipse or Gaussian ellipsoid) to represent object surfaces during their reconstruction. In this paper, we highlight that this can be insufficient for object surfaces to be represented in high quality. Thus, we propose a novel framework that, for the first time, enables Gaussian Splatting to incorporate multiple types of (geometrical) primitives during its surface reconstruction process. Specifically, in our framework, we first propose a compositional splatting strategy, enabling the splatting and rendering of different types of primitives in the Gaussian Splatting pipeline. In addition, we also design our framework with a mixed-primitive-based initialization strategy and a vertex pruning mechanism to further promote its surface representation learning process to be well executed leveraging different types of primitives. Extensive experiments show the efficacy of our framework and its accurate surface reconstruction 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。
