3D Gabor Splatting: Reconstruction of High-frequnecy Surface Texture using Gabor Noise

3D Gaussian splatting has experienced explosive popularity in the past few years in the field of novel view synthesis. The lightweight and differentiable representation of the radiance field using the Gaussian enables rapid and high-quality reconstruction and fast rendering. However, reconstructing objects with high-frequency surface textures (e.g., fine stripes) requires many skinny Gaussian kernels because each Gaussian represents only one color if viewed from one direction. Thus, reconstructing the stripes pattern, for example, requires Gaussians for at least the number of stripes. We present 3D Gabor splatting, which augments the Gaussian kernel to represent spatially high-frequency signals using Gabor noise. The Gabor kernel is a combination of a Gaussian term and spatially fluctuating wave functions, making it suitable for representing spatial high-frequency texture. We demonstrate that our 3D Gabor splatting can reconstruct various high-frequency textures on the objects.

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Publication Details

Journal
Eurographics
Published
2025-01-01
DOI
https://doi.org/10.2312/egs.20251040
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
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article

3D Gabor Splatting: Reconstruction of High-frequnecy Surface Texture using Gabor Noise

Eurographics
Computer Graphics and Visualization Techniques
article

3D Gabor Splatting: Reconstruction of High-frequnecy Surface Texture using Gabor Noise

article en

Abstract

3D Gaussian splatting has experienced explosive popularity in the past few years in the field of novel view synthesis. The lightweight and differentiable representation of the radiance field using the Gaussian enables rapid and high-quality reconstruction and fast rendering. However, reconstructing objects with high-frequency surface textures (e.g., fine stripes) requires many skinny Gaussian kernels because each Gaussian represents only one color if viewed from one direction. Thus, reconstructing the stripes pattern, for example, requires Gaussians for at least the number of stripes. We present 3D Gabor splatting, which augments the Gaussian kernel to represent spatially high-frequency signals using Gabor noise. The Gabor kernel is a combination of a Gaussian term and spatially fluctuating wave functions, making it suitable for representing spatial high-frequency texture. We demonstrate that our 3D Gabor splatting can reconstruct various high-frequency textures on the objects.

Eurographics
The University of Tokyo (JP)
Sustainable cities and communities
Openalex Percentile: Top 39%
Computer Graphics and Visualization Techniques
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