基于网格的渲染：利用高斯溅射初始化的网格化
MeshSplats: Mesh-Based Rendering with Gaussian Splatting Initialization
AI总结：
本文提出MeshSplats方法，将高斯溅射转化为网格格式，利用光线追踪实现高效渲染，同时通过优化算法提升质量，适用于计算机图形学和图像处理。
摘要：
高斯溅射（GS）是3D计算机图形学中的重要技术。基于GS的算法几乎都绕过了传统的光线追踪等方法，这些方法在渲染中有诸多固有优势。例如，光线追踪可以处理不相干光线以实现高级照明效果，包括阴影和反射。为了解决这一限制，我们引入MeshSplats方法，将GS转换为网格格式。在训练完成后，MeshSplats将高斯元素转换为网格面，使能够利用光线追踪方法进行渲染，利用其所有相关优势。我们的模型在转换后即可使用，生成略微降低的重建质量的网格，无需额外训练。此外，我们可以通过在网格面上而非高斯组件上应用专用优化算法来提升质量。重要的是，MeshSplats作为封装器，将预训练的GS模型转换为可光线追踪的格式。我们的方法的有效性通过实验结果得到验证，凸显了其在计算机图形学和图像处理中的广泛应用。
英文摘要：
Gaussian Splatting (GS) is a recent and pivotal technique in 3D computer graphics. GS-based algorithms almost always bypass classical methods such as ray tracing, which offer numerous inherent advantages for rendering. For example, ray tracing can handle incoherent rays for advanced lighting effects, including shadows and reflections. To address this limitation, we introduce MeshSplats, a method which converts GS to a mesh-like format. Following the completion of training, MeshSplats transforms Gaussian elements into mesh faces, enabling rendering using ray tracing methods with all their associated benefits. Our model can be utilized immediately following transformation, yielding a mesh of slightly reduced reconstruction quality without additional training. Furthermore, we can enhance the quality by applying a dedicated optimization algorithm that operates on mesh faces rather than Gaussian components. Importantly, MeshSplats acts as a wrapper, converting pre-trained GS models into a ray-traceable format. The efficacy of our method is substantiated by experimental results, underscoring its extensive applications in computer graphics and image processing.
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。
