通过多视角法向与距离约束，提升3D高斯溅射的表面重建精度。
Multi-view Normal and Distance Guidance Gaussian Splatting for Surface Reconstruction
- 引入多视角距离重投影正则化，实现不同视角间高斯点对齐。
- 设计法向一致性增强模块，减少视图切换时的几何偏差。
- 适用于小规模室内外场景，显著改善重建质量，适合3D重建研究者。
3D高斯溅射（3DGS）在表面重建领域取得了显著成果。然而，当高斯法向量在单视角投影平面内对齐时，虽然当前视角的几何外观合理，但在切换到邻近视角时可能产生偏差。为解决多视角场景中的距离和全局匹配挑战，我们提出了多视角法向与距离引导的高斯溅射方法。该方法通过约束邻近深度图并对齐3D法向量，实现了几何深度统一与高精度重建。具体而言，针对小规模室内外场景，我们设计了多视角距离重投影正则化模块，通过计算两个邻近视角与同一高斯表面间的距离损失，实现多视角高斯对齐。同时，提出多视角法向增强模块，通过匹配邻近视角中像素点的法向量并计算损失，确保跨视角的一致性。大量实验结果表明，该方法在定量与定性评估上均优于基线，显著提升了3DGS的表面重建能力。代码将公开于https://github.com/Bistu3DV/MND-GS/。
原文摘要 · Abstract (English)
3D Gaussian Splatting (3DGS) achieves remarkable results in the field of surface reconstruction. However, when Gaussian normal vectors are aligned within the single-view projection plane, while the geometry appears reasonable in the current view, biases may emerge upon switching to nearby views. To address the distance and global matching challenges in multi-view scenes, we design multi-view normal and distance-guided Gaussian splatting. This method achieves geometric depth unification and high-accuracy reconstruction by constraining nearby depth maps and aligning 3D normals. Specifically, for the reconstruction of small indoor and outdoor scenes, we propose a multi-view distance reprojection regularization module that achieves multi-view Gaussian alignment by computing the distance loss between two nearby views and the same Gaussian surface. Additionally, we develop a multi-view normal enhancement module, which ensures consistency across views by matching the normals of pixel points in nearby views and calculating the loss. Extensive experimental results demonstrate that our method outperforms the baseline in both quantitative and qualitative evaluations, significantly enhancing the surface reconstruction capability of 3DGS. Our code will be made publicly available at (https://github.com/Bistu3DV/MND-GS/).
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