标题： 带有法线信息的3D高斯泼溅用于网格提取和渲染优化 显示英文标题

标题： 3D Gaussian Splatting with Normal Information for Mesh Extraction and Improved Rendering

摘要： 可微分的3D高斯点云渲染作为一种高效的灵活渲染技术，已从一组2D视图中出现，用于表示复杂场景并实现高质量的实时新视角合成。 然而，它依赖于光度损失可能导致几何结构和提取的网格不精确，特别是在高曲率或细节丰富的区域。 我们提出了一种新的正则化方法，使用从高斯中估计的符号距离函数的梯度，以在提高渲染质量的同时提取表面网格。 正则化的法线监督有助于更好的渲染和网格重建，这对于视频生成、动画、AR-VR和游戏中的下游应用至关重要。 我们在Mip-NeRF360、Tanks and Temples和Deep-Blending等数据集上展示了我们方法的有效性。 与其它网格提取渲染方法相比，我们的方法在逼真度指标上得分更高，而不会影响网格质量。 显示英文摘要

摘要： Differentiable 3D Gaussian splatting has emerged as an efficient and flexible rendering technique for representing complex scenes from a collection of 2D views and enabling high-quality real-time novel-view synthesis. However, its reliance on photometric losses can lead to imprecisely reconstructed geometry and extracted meshes, especially in regions with high curvature or fine detail. We propose a novel regularization method using the gradients of a signed distance function estimated from the Gaussians, to improve the quality of rendering while also extracting a surface mesh. The regularizing normal supervision facilitates better rendering and mesh reconstruction, which is crucial for downstream applications in video generation, animation, AR-VR and gaming. We demonstrate the effectiveness of our approach on datasets such as Mip-NeRF360, Tanks and Temples, and Deep-Blending. Our method scores higher on photorealism metrics compared to other mesh extracting rendering methods without compromising mesh quality.