GS-Octree: Octree-based 3D Gaussian Splatting for Robust Object-level 3D Reconstruction Under Strong Lighting
The 3D Gaussian Splatting technique has significantly advanced the construction of radiance fields from multi-view images, enabling real-time rendering. While point-based rasterization effectively reduces computational demands for rendering, it often struggles to accurately reconstruct the geometry of the target object, especially under strong lighting. To address this challenge, we introduce a novel approach that combines octree-based implicit surface representations with Gaussian splatting. Our method consists of four stages. Initially, it reconstructs a signed distance field (SDF) and a radiance field through volume rendering, encoding them in a low-resolution octree. The initial SDF represents the coarse geometry of the target object. Subsequently, it introduces 3D Gaussians as additional degrees of freedom, which are guided by the SDF. In the third stage, the optimized Gaussians further improve the accuracy of the SDF, allowing it to recover finer geometric details compared to the initial SDF obtained in the first stage. Finally, it adopts the refined SDF to further optimize the 3D Gaussians via splatting, eliminating those that contribute little to visual appearance. Experimental results show that our method, which leverages the distribution of 3D Gaussians with SDFs, reconstructs more accurate geometry, particularly in images with specular highlights caused by strong lighting.
3D高斯散射技术在多视角图像构建辐射场方面取得了重大进展，使实时渲染成为可能。尽管基于点的光栅化有效地降低了渲染的计算需求，但它经常难以准确重建目标对象的几何形状，特别是在强照明下。为了应对这一挑战，我们引入了一种将基于八叉树的隐式表面表示与高斯散射结合的新方法。我们的方法包括四个阶段。起初，它通过体积渲染重建了一个符号距离场（SDF）和一个辐射场，并将它们编码在一个低分辨率的八叉树中。初始SDF代表了目标对象的粗糙几何形状。随后，它引入了3D高斯作为额外的自由度，这些高斯由SDF指导。在第三阶段，优化后的高斯进一步提高了SDF的准确性，使其能够恢复比第一阶段获得的初始SDF更细致的几何细节。最后，它采用了精炼的SDF来进一步优化3D高斯散射，淘汰那些对视觉外观贡献甚微的高斯。实验结果表明，我们的方法利用3D高斯与SDF的分布，特别是在有强照明引起的镜面高光的图像中，能够重建更精确的几何形状。