mlsanityData to 14 Oct 2026

GUS-IR: Gaussian Splatting with Unified Shading for Inverse Rendering

arXiv 2411.07478 ↗First posted 12 Nov 2024cs.CVcited by 11

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Abstract (arXiv)

Recovering the intrinsic physical attributes of a scene from images, generally termed as the inverse rendering problem, has been a central and challenging task in computer vision and computer graphics. In this paper, we present GUS-IR, a novel framework designed to address the inverse rendering problem for complicated scenes featuring rough and glossy surfaces. This paper starts by analyzing and comparing two prominent shading techniques popularly used for inverse rendering, forward shading and deferred shading, effectiveness in handling complex materials. More importantly, we propose a unified shading solution that combines the advantages of both techniques for better decomposition. In addition, we analyze the normal modeling in 3D Gaussian Splatting (3DGS) and utilize the shortest axis as normal for each particle in GUS-IR, along with a depth-related regularization, resulting in improved geometric representation and better shape reconstruction. Furthermore, we enhance the probe-based baking scheme proposed by GS-IR to achieve more accurate ambient occlusion modeling to better handle indirect illumination. Extensive experiments have demonstrated the superior performance of GUS-IR in achieving precise intrinsic decomposition and geometric representation, supporting many downstream tasks (such as relighting, retouching) in computer vision, graphics, and extended reality.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 45 of its 80 references that are in the map. First posted on arXiv 12 Nov 2024.

Builds on

45 of 80 references.

References · 45

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33 more
  1. 2021Volume Rendering of Neural Implicit Surfacescited by 996
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  13. 2023GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfacescited by 252
  14. 2023GS-IR: 3D Gaussian Splatting for Inverse Renderingcited by 224
  15. 2021Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decompositioncited by 205
  16. 2021Deblur-NeRF: Neural Radiance Fields from Blurry Imagescited by 179
  17. 2023TensoIR: Tensorial Inverse Renderingcited by 168
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 6; 2026: 5.

11 papers.