GUS-IR: Gaussian Splatting with Unified Shading for Inverse Rendering
Not on the map. Why?
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
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
- 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
- 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,964
- 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,712
- 2022TensoRF: Tensorial Radiance Fieldscited by 1,280
- 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,219
- 20234D Gaussian Splatting for Real-Time Dynamic Scene Renderingcited by 1,157
- 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,076
33 more
- 2021Volume Rendering of Neural Implicit Surfacescited by 996
- 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 964
- 2023K-Planes: Explicit Radiance Fields in Space, Time, and Appearancecited by 746
- 2023HexPlane: A Fast Representation for Dynamic Scenescited by 587
- 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 575
- 2022Point-NeRF: Point-based Neural Radiance Fieldscited by 503
- 2020NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesiscited by 496
- 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 470
- 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 460
- 2020NeRD: Neural Reflectance Decomposition from Image Collectionscited by 449
- 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 366
- 2021PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relightingcited by 335
- 2023GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfacescited by 252
- 2023GS-IR: 3D Gaussian Splatting for Inverse Renderingcited by 224
- 2021Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decompositioncited by 205
- 2021Deblur-NeRF: Neural Radiance Fields from Blurry Imagescited by 179
- 2023TensoIR: Tensorial Inverse Renderingcited by 168
- 2022Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoisingcited by 163
- 2023NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects from Multiview Imagescited by 163
- 2023Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracingcited by 142
- 2022NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priorscited by 125
- 2022IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Imagescited by 111
- 2024RaDe-GS: Rasterizing Depth in Gaussian Splattingcited by 111
- 2020Deep Reflectance Volumes: Relightable Reconstructions from Multi-View Photometric Imagescited by 98
- 2021Unified Shape and SVBRDF Recovery using Differentiable Monte Carlo Renderingcited by 71
- 2020Deep 3D Capture: Geometry and Reflectance from Sparse Multi-View Imagescited by 65
- 2023ENVIDR: Implicit Differentiable Renderer with Neural Environment Lightingcited by 65
- 2019Planar Prior Assisted PatchMatch Multi-View Stereocited by 57
- 2019TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereocited by 34
- 2024IllumiNeRF: 3D Relighting Without Inverse Renderingcited by 29
- 2023HelixSurf: A Robust and Efficient Neural Implicit Surface Learning of Indoor Scenes with Iterative Intertwined Regularizationcited by 20
- 2024Objects With Lighting: A Real-World Dataset for Evaluating Reconstruction and Rendering for Object Relightingcited by 18
- 2024Sur2f: A Hybrid Representation for High-Quality and Efficient Surface Reconstruction from Multi-view Imagescited by 5
Built on by
Citing papers per year: 2025: 6; 2026: 5.
11 papers.
- 2025RTR-GS: 3D Gaussian Splatting for Inverse Rendering with Radiance Transfer and Reflectioncited by 10
- 2026LuxRemix: Lighting Decomposition and Remixing for Indoor Scenescited by 9
- 2025RelightMaster: Precise Video Relighting with Multi-plane Light Imagescited by 8
- 2025HumanOLAT: A Large-Scale Dataset for Full-Body Human Relighting and Novel-View Synthesiscited by 7
- 2025Training-Free Multi-View Extension of IC-Light for Textual Position-Aware Scene Relightingcited by 2
- 2025Yesnt: Are Diffusion Relighting Models Ready for Capture Stage Compositing? A Hybrid Alternative to Bridge the Gapcited by 1
- 2025High Dynamic Range 3D Gaussian Splatting via Luminance-Chromaticity Decompositioncited by 1
- 2026SeasonScapes: Learning Large-scale Re-lightable 3D Landscapes with Seasonal Variation from Sparse Webcamscited by 0
- 2026Denoising-GS: Gaussian Splatting with Spatial-aware Denoisingcited by 0
- 2026TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructionscited by 0
- 2026From Sparse and Imperfect 2D Anchors to Consistent 3D Gaussian Street Scenes: Support-Aware Appearancecited by 0
- 2026From Sparse and Imperfect 2D Anchors to Consistent 3D Gaussian Street Scenes: Support-Aware Appearance24 Jun 2026
- 2026TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructions9 Jun 2026
- 2026Denoising-GS: Gaussian Splatting with Spatial-aware Denoising14 May 2026
- 2026SeasonScapes: Learning Large-scale Re-lightable 3D Landscapes with Seasonal Variation from Sparse Webcams9 May 2026
- 2026LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes21 Jan 2026
- 2025Training-Free Multi-View Extension of IC-Light for Textual Position-Aware Scene Relighting17 Nov 2025
- 2025High Dynamic Range 3D Gaussian Splatting via Luminance-Chromaticity Decomposition17 Nov 2025
- 2025RelightMaster: Precise Video Relighting with Multi-plane Light Images9 Nov 2025
- 2025Yesnt: Are Diffusion Relighting Models Ready for Capture Stage Compositing? A Hybrid Alternative to Bridge the Gap27 Oct 2025
- 2025HumanOLAT: A Large-Scale Dataset for Full-Body Human Relighting and Novel-View Synthesis12 Aug 2025
- 2025RTR-GS: 3D Gaussian Splatting for Inverse Rendering with Radiance Transfer and Reflection10 Jul 2025