MVG-Splatting：基于自适应分位数几何一致性致密化的多视图引导高斯泼溅
MVG-Splatting: Multi-View Guided Gaussian Splatting with Adaptive Quantile-Based Geometric Consistency Densification
AI总结：
针对2DGS压缩导致的渲染质量下降和深度计算不一致问题，提出MVG-Splatting，通过优化法线计算和自适应分位数致密化，实现高质量网格直接提取，提升三维重建保真度。
摘要：
在快速发展的三维重建领域，三维高斯泼溅（3DGS）和二维高斯泼溅（2DGS）代表了显著的进步。尽管2DGS将三维高斯基元压缩为二维高斯面片以有效提升网格提取质量，但这种压缩可能潜在地导致渲染质量的下降。此外，不可靠的致密化过程以及通过不透明度累积计算深度的方法可能损害网格提取的细节。为解决此问题，我们引入了MVG-Splatting，一种由多视图考量引导的解决方案。具体而言，我们整合了一种优化的法线计算方法，该方法与图像梯度相结合，有助于纠正原始深度计算中的不一致性。此外，利用类似于多视图立体（MVS）中的投影策略，我们提出了一种基于自适应分位数的方法，该方法由深度图引导，动态确定从粗到细的额外致密化水平。实验证据表明，我们的方法不仅解决了由深度差异引起的渲染质量下降问题，而且促进了使用行进立方体算法从密集高斯点云直接提取网格。该方法显著提升了三维重建过程的整体保真度和准确性，确保了几何细节和视觉质量。
英文摘要：
In the rapidly evolving field of 3D reconstruction, 3D Gaussian Splatting (3DGS) and 2D Gaussian Splatting (2DGS) represent significant advancements. Although 2DGS compresses 3D Gaussian primitives into 2D Gaussian surfels to effectively enhance mesh extraction quality, this compression can potentially lead to a decrease in rendering quality. Additionally, unreliable densification processes and the calculation of depth through the accumulation of opacity can compromise the detail of mesh extraction. To address this issue, we introduce MVG-Splatting, a solution guided by Multi-View considerations. Specifically, we integrate an optimized method for calculating normals, which, combined with image gradients, helps rectify inconsistencies in the original depth computations. Additionally, utilizing projection strategies akin to those in Multi-View Stereo (MVS), we propose an adaptive quantile-based method that dynamically determines the level of additional densification guided by depth maps, from coarse to fine detail. Experimental evidence demonstrates that our method not only resolves the issues of rendering quality degradation caused by depth discrepancies but also facilitates direct mesh extraction from dense Gaussian point clouds using the Marching Cubes algorithm. This approach significantly enhances the overall fidelity and accuracy of the 3D reconstruction process, ensuring that both the geometric details and visual quality.
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。
