用偏振信息提升3D高斯点云的物理真实感，实现更精准的材质重建与光照重演。
PhyGaP: Physically-Grounded Gaussians with Polarization Cues
- 引入偏振光线索，改进延迟渲染流程以分解反射特性。
- 在合成与真实场景中平均提升PSNR约2 dB，法向误差降低45.7%。
- 适合需要高保真光照重演的工业级3D重建任务。
近期3D高斯点云（3DGS）在通过延迟渲染（DR）建模反射物体及其环境交互方面取得显著进展。然而，现有方法常难以准确重建反照率与反射率等物理属性，导致无法支持高保真光照重演。由于RGB图像缺乏形状与材质信息，我们提出PhyGaP，一种基于物理约束的3DGS方法，利用偏振线索实现精确的反射分解与视觉一致的光照重演。具体地，设计了极化延迟渲染（PolarDR）过程以建模反射偏振特性，并提出自遮挡感知的环境图构建技术（GridMap），解决非凸物体的间接光照问题。在多个合成与真实场景中验证，即使仅有部分偏振线索，PhyGaP在重建物体外观与表面法向方面表现优异（相比现有基于RGB的方法，平均PSNR提升约2 dB，余弦距离改善45.7%），并达到领先的逆渲染与光照重演性能。代码将很快开源。
原文摘要 · Abstract (English)
Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated great success in modeling reflective 3D objects and their interaction with the environment via deferred rendering (DR). However, existing methods often struggle with correctly reconstructing physical attributes such as albedo and reflectance, and therefore they do not support high-fidelity relighting. Observing that this limitation stems from the lack of shape and material information in RGB images, we present PhyGaP, a physically-grounded 3DGS method that leverages polarization cues to facilitate precise reflection decomposition and visually consistent relighting of reconstructed objects. Specifically, we design a polarimetric deferred rendering (PolarDR) process to model polarization by reflection, and a self-occlusion-aware environment map building technique (GridMap) to resolve indirect lighting of non-convex objects. We validate on multiple synthetic and real-world scenes, including those featuring only partial polarization cues, that PhyGaP not only excels in reconstructing the appearance and surface normal of reflective 3D objects (~2 dB in PSNR and 45.7% in Cosine Distance better than existing RGB-based methods on average), but also achieves state-of-the-art inverse rendering and relighting capability. Our code will be released soon.
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