GeoSplatting: Towards Geometry Guided Gaussian Splatting for Physically-based Inverse Rendering

TL;DR

GeoSplatting introduces a geometry-guided Gaussian Splatting method that enhances physically-based inverse rendering by explicitly modeling geometry, leading to more accurate material decomposition and relighting in 3D scene representations.

Contribution

The paper proposes GeoSplatting, a novel technique that integrates explicit geometric guidance into 3D Gaussian Splatting for improved light transport modeling and material disentanglement.

Findings

Achieves more accurate material decomposition and relighting.

Demonstrates superior efficiency and state-of-the-art inverse rendering performance.

Effectively models light transport with geometry guidance.

Abstract

Recent 3D Gaussian Splatting (3DGS) representations have demonstrated remarkable performance in novel view synthesis; further, material-lighting disentanglement on 3DGS warrants relighting capabilities and its adaptability to broader applications. While the general approach to the latter operation lies in integrating differentiable physically-based rendering (PBR) techniques to jointly recover BRDF materials and environment lighting, achieving a precise disentanglement remains an inherently difficult task due to the challenge of accurately modeling light transport. Existing approaches typically approximate Gaussian points' normals, which constitute an implicit geometric constraint. However, they usually suffer from inaccuracies in normal estimation that subsequently degrade light transport, resulting in noisy material decomposition and flawed relighting results. To address this, we propose GeoSplatting, a novel approach that augments 3DGS with explicit geometry guidance for precise light transport modeling. By differentiably constructing a surface-grounded 3DGS from an optimizable mesh, our approach leverages well-defined mesh normals and the opaque mesh surface, and additionally facilitates the use of mesh-based ray tracing techniques for efficient, occlusion-aware light transport calculations. This enhancement ensures precise material decomposition while preserving the efficiency and high-quality rendering capabilities of 3DGS. Comprehensive evaluations across diverse datasets demonstrate the effectiveness of GeoSplatting, highlighting its superior efficiency and state-of-the-art inverse rendering performance. The project page can be found at https://pku-vcl-geometry.github.io/GeoSplatting/.