PolGS: Polarimetric Gaussian Splatting for Fast Reflective Surface Reconstruction

Efficient shape reconstruction for surfaces with complex reflectance properties is crucial for real-time virtual reality. While 3D Gaussian Splatting (3DGS)-based methods offer fast novel view rendering by leveraging their explicit surface representation, their reconstruction quality lags behind that of implicit neural representations, particularly in the case of recovering surfaces with complex reflective reflectance. To address these problems, we propose PolGS, a $\underline{Pol}$ arimetric $\underline{G}$ aussian $\underline{Sp}$ latting model allowing fast reflective surface reconstruction in 10 minutes. By integrating polarimetric constraints into the 3DGS framework, PolGS effectively separates specular and diffuse components, enhancing reconstruction quality for challenging reflective materials. Experimental results on the synthetic and real-world dataset validate the effectiveness of our method. Project page: https://yu-fei-han.github.io/polgs. Figure 1. Comparison of efficiency and accuracy on reflective surface reconstruction. Our method takes the shortest time while comparable shape reconstruction accuracy (measured by Chamfer Distance in millimeters) with the existing method based on neural implicit surface representation [23].