GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfaces

Yingwenqi Jiang, Jiadong Tu, Yuan Liu, Xifeng Gao, Xiaoxiao Long*, Wenping Wang, Yuexin Ma*

*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

Abstract

The advent of neural 3D Gaussians [21] has recently brought about a revolution in the field of neural rendering, facilitating the generation of high-quality renderings at real-time speeds. However, the explicit and discrete repre-sentation encounters challenges when applied to scenes fea-turing reflective surfaces. In this paper, we present Gaus-sian Shader, a novel method that applies a simplified shading function on 3D Gaussians to enhance the neural ren-dering in scenes with reflective surfaces while preserving the training and rendering efficiency. The main challenge in applying the shading function lies in the accurate nor-mal estimation on discrete 3D Gaussians. Specifically, we proposed a novel normal estimation framework based on the shortest axis directions of 3D Gaussians with a deli-cately designed loss to make the consistency between the normals and the geometries of Gaussian spheres. Experiments show that GaussianShader strikes a commendable balance between efficiency and visual quality. Our method surpasses Gaussian Splatting [21] in PSNR on specular object datasets, exhibiting an improvement of 1.57dB. When compared to prior works handling reflective surfaces, such as Ref-NeRF [45], our optimization time is significantly accelerated (23h vs. 0.58h).

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024
PublisherIEEE Computer Society
Pages5322-5332
Number of pages11
ISBN (Electronic)9798350353006
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024 - Seattle, United States
Duration: 16 Jun 202422 Jun 2024

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Conference

Conference2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024
Country/TerritoryUnited States
CitySeattle
Period16/06/2422/06/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

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