CVDec 8, 2023

GIR: 3D Gaussian Inverse Rendering for Relightable Scene Factorization

Peking U
arXiv:2312.05133v299 citationsh-index: 60Has CodeIEEE Trans Pattern Anal Mach Intell
Originality Highly original
AI Analysis

This enables real-time interactive graphics applications like material editing and relighting, representing a strong specific gain in the domain.

The paper tackles 3D inverse rendering by factorizing scenes into material, light, and geometry using 3D Gaussians, achieving state-of-the-art performance in relighting and novel view synthesis with real-time rendering.

This paper presents a 3D Gaussian Inverse Rendering (GIR) method, employing 3D Gaussian representations to effectively factorize the scene into material properties, light, and geometry. The key contributions lie in three-fold. We compute the normal of each 3D Gaussian using the shortest eigenvector, with a directional masking scheme forcing accurate normal estimation without external supervision. We adopt an efficient voxel-based indirect illumination tracing scheme that stores direction-aware outgoing radiance in each 3D Gaussian to disentangle secondary illumination for approximating multi-bounce light transport. To further enhance the illumination disentanglement, we represent a high-resolution environmental map with a learnable low-resolution map and a lightweight, fully convolutional network. Our method achieves state-of-the-art performance in both relighting and novel view synthesis tasks among the recently proposed inverse rendering methods while achieving real-time rendering. This substantiates our proposed method's efficacy and broad applicability, highlighting its potential as an influential tool in various real-time interactive graphics applications such as material editing and relighting. The code will be released at https://github.com/guduxiaolang/GIR.

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