GI-GS: Global Illumination Decomposition on Gaussian Splatting for Inverse Rendering
- URL: http://arxiv.org/abs/2410.02619v1
- Date: Thu, 3 Oct 2024 15:58:18 GMT
- Title: GI-GS: Global Illumination Decomposition on Gaussian Splatting for Inverse Rendering
- Authors: Hongze Chen, Zehong Lin, Jun Zhang,
- Abstract summary: We present GI-GS, a novel inverse rendering framework that leverages 3D Gaussian Splatting (3DGS) and deferred shading.
In our framework, we first render a G-buffer to capture the detailed geometry and material properties of the scene.
With the G-buffer and previous rendering results, the indirect lighting can be calculated through a lightweight path tracing.
- Score: 6.820642721852439
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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 relighting. Quantitative and qualitative results show that our GI-GS outperforms existing baselines in both rendering quality and efficiency.
Related papers
- GUS-IR: Gaussian Splatting with Unified Shading for Inverse Rendering [83.69136534797686]
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.
We propose a unified shading solution that combines the advantages of both techniques for better decomposition.
arXiv Detail & Related papers (2024-11-12T01:51:05Z) - GS-ID: Illumination Decomposition on Gaussian Splatting via Diffusion Prior and Parametric Light Source Optimization [4.928698209254161]
We present GS-ID, a novel framework for illumination decomposition on Gaussian Splatting.
GS-ID produces state-of-the-art illumination decomposition results while achieving better geometry reconstruction and rendering performance.
arXiv Detail & Related papers (2024-08-16T04:38:31Z) - GS-Phong: Meta-Learned 3D Gaussians for Relightable Novel View Synthesis [63.5925701087252]
We propose a novel method for representing a scene illuminated by a point light using a set of relightable 3D Gaussian points.
Inspired by the Blinn-Phong model, our approach decomposes the scene into ambient, diffuse, and specular components.
To facilitate the decomposition of geometric information independent of lighting conditions, we introduce a novel bilevel optimization-based meta-learning framework.
arXiv Detail & Related papers (2024-05-31T13:48:54Z) - DeferredGS: Decoupled and Editable Gaussian Splatting with Deferred Shading [50.331929164207324]
We introduce DeferredGS, a method for decoupling and editing the Gaussian splatting representation using deferred shading.
Both qualitative and quantitative experiments demonstrate the superior performance of DeferredGS in novel view and editing tasks.
arXiv Detail & Related papers (2024-04-15T01:58:54Z) - GIR: 3D Gaussian Inverse Rendering for Relightable Scene Factorization [62.13932669494098]
This paper presents a 3D Gaussian Inverse Rendering (GIR) method, employing 3D Gaussian representations to factorize the scene into material properties, light, and geometry.
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.
arXiv Detail & Related papers (2023-12-08T16:05:15Z) - Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracing [21.498078188364566]
We present a novel differentiable point-based rendering framework to achieve photo-realistic relighting.
The proposed framework showcases the potential to revolutionize the mesh-based graphics pipeline with a point-based pipeline enabling editing, tracing, and relighting.
arXiv Detail & Related papers (2023-11-27T18:07:58Z) - GS-IR: 3D Gaussian Splatting for Inverse Rendering [71.14234327414086]
We propose GS-IR, a novel inverse rendering approach based on 3D Gaussian Splatting (GS)
We extend GS, a top-performance representation for novel view synthesis, to estimate scene geometry, surface material, and environment illumination from multi-view images captured under unknown lighting conditions.
The flexible and expressive GS representation allows us to achieve fast and compact geometry reconstruction, photorealistic novel view synthesis, and effective physically-based rendering.
arXiv Detail & Related papers (2023-11-26T02:35:09Z) - DIB-R++: Learning to Predict Lighting and Material with a Hybrid
Differentiable Renderer [78.91753256634453]
We consider the challenging problem of predicting intrinsic object properties from a single image by exploiting differentiables.
In this work, we propose DIBR++, a hybrid differentiable which supports these effects by combining specularization and ray-tracing.
Compared to more advanced physics-based differentiables, DIBR++ is highly performant due to its compact and expressive model.
arXiv Detail & Related papers (2021-10-30T01:59:39Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.