Abstract
Reconstructing translucent objects from multi-view images is a difficult problem. Previously, researchers have used differentiable path tracing and the neural implicit field, which require relatively large computational costs. Recently, many works have achieved good reconstruction results for opaque objects based on a 3DGS pipeline with much higher efficiency. However, such methods have difficulty dealing with translucent objects, because they do not consider the optical properties of translucent objects. In this paper, we propose a novel 3DGS-based pipeline (GTSR) to reconstruct the surface geometry of translucent objects. GTSR combines two sets of Gaussians, surface and interior Gaussians, which are used to model the surface and scattering color when lights pass translucent objects. To render the appearance of translucent objects, we introduce a method that uses the Fresnel term to blend two sets of Gaussians. Furthermore, to improve the reconstructed details of non-contour areas, we introduce the Disney BSDF model with deferred rendering to enhance constraints of the normal and depth. Experimental results demonstrate that our method outperforms baseline reconstruction methods on the NeuralTO Syn dataset while showing great real-time rendering performance. We also extend the dataset with new translucent objects of varying material properties and demonstrate our method can adapt to different translucent materials.
Abstract (translated)
从多视角图像重建半透明物体是一个难题。此前，研究者们采用可微路径追踪与神经隐式场等方法，但这些方案需要较高的计算成本。近期，许多基于3D高斯泼溅（3DGS）管线的方法在高效重建不透明物体方面取得了良好效果。然而，此类方法难以处理半透明物体，因其未考虑半透明物体的光学特性。本文提出一种基于3DGS的新管线（GTSR），用于重建半透明物体的表面几何结构。GTSR结合了两组高斯元——表面高斯元与内部高斯元，分别用于建模半透明物体表面的反射光与光线穿透后的散射颜色。为渲染半透明物体外观，我们引入基于菲涅尔项混合两组高斯元的方法。此外，为提升非轮廓区域的重建细节，我们采用迪士尼双向散射分布函数（BSDF）模型结合延迟渲染技术，增强对法线与深度的约束。实验结果表明，在NeuralTO Syn合成数据集上，本方法优于基线重建方法，同时展现出优秀的实时渲染性能。我们还扩展了包含不同材质特性的新半透明物体数据集，并验证了本方法可适应多种半透明材质。
URL
https://arxiv.org/abs/2603.22036
