GI-GS: Global Illumination Decomposition on Gaussian Splatting for Inverse Rendering

  • Hongze CHEN
  • , Zehong LIN*
  • , Jun ZHANG
  • *Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

3 Citations (Scopus)

Abstract

We present GI-GS, a novel inverse rendering framework that leverages 3D Gaussian Splatting (3DGS) and deferred shading to achieve photo-realistic novel view synthesis and relighting. In inverse rendering, accurately modeling the shading processes of objects is essential for achieving high-fidelity results. Therefore, it is critical to incorporate global illumination to account for indirect lighting that reaches an object after multiple bounces across the scene. Previous 3DGS-based methods have attempted to model indirect lighting by characterizing indirect illumination as learnable lighting volumes or additional attributes of each Gaussian, while using baked occlusion to represent shadow effects. These methods, however, fail to accurately model the complex physical interactions between light and objects, making it impossible to construct realistic indirect illumination during relighting. To address this limitation, we propose to calculate indirect lighting using efficient path tracing with deferred shading. In our framework, we first render a G-buffer to capture the detailed geometry and material properties of the scene. Then, we perform physically-based rendering (PBR) only for direct lighting. With the G-buffer and previous rendering results, the indirect lighting can be calculated through a lightweight path tracing. Our method effectively models indirect lighting under any given lighting conditions, thereby achieving better novel view synthesis and competitive relighting. Quantitative and qualitative results show that our GI-GS outperforms existing baselines in both rendering quality and efficiency. Project page: https://stopaimme.github.io/GI-GS-site/.

Original languageEnglish
Title of host publication13th International Conference on Learning Representations, ICLR 2025
PublisherInternational Conference on Learning Representations, ICLR
Pages41825-41854
Number of pages30
ISBN (Electronic)9798331320850
Publication statusPublished - 2025
Externally publishedYes
Event13th International Conference on Learning Representations, ICLR 2025 - Singapore EXPO, Singapore, Singapore
Duration: 24 Apr 202528 Apr 2025
https://iclr.cc/

Conference

Conference13th International Conference on Learning Representations, ICLR 2025
Country/TerritorySingapore
CitySingapore
Period24/04/2528/04/25
Internet address

Bibliographical note

Publisher Copyright:
© 2025 13th International Conference on Learning Representations, ICLR 2025. All rights reserved.

Keywords

  • Inverse rendering
  • Gaussian Splatting
  • Relighting

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