360-GS: Layout-Guided Panoramic Gaussian Splatting for Indoor Roaming

3D Gaussian Splatting (3D-GS) has recently attracted great attention with real-time and photo-realistic renderings. This technique typically takes perspective images as input and optimizes a set of 3D elliptical Gaussians by splatting them onto the image planes, resulting in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$2 D$</tex> Gaussians. However, applying 3D-GS to panoramic inputs presents challenges in effectively modeling the projection onto the spherical surface of 360° images using 2D Gaussians. In practical applications, input panoramas are often sparse, leading to unreliable initialization of 3D Gaussians and subsequent degradation of 3D-GS quality. In addition, due to the under-constrained geometry of texture-less planes (e.g., walls and floors), 3D-GS struggles to model these flat regions with elliptical Gaussians, resulting in significant floaters in novel views. To address these issues, we propose 360-GS, a novel layout-guided 360° Gaussian splatting for a limited set of panoramic inputs. Instead of splatting 3D Gaussians directly onto the spherical surface, 360-GS projects them onto the tangent plane of the unit sphere and then maps them to the spherical projections.

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Publication Details

Published
2025-03-25
DOI
https://doi.org/10.1109/3dv66043.2025.00101
Citations
4
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
14.16
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article

360-GS: Layout-Guided Panoramic Gaussian Splatting for Indoor Roaming

Yanwen Guo, Yuanqi Li, Letian Huang, Jie Guo et al.
4 citations
Computer Graphics and Visualization Techniques
14.16
article

360-GS: Layout-Guided Panoramic Gaussian Splatting for Indoor Roaming

Yanwen Guo, Yuanqi Li, Letian Huang, Jie Guo, Jiayang Bai, Wen Gong
article en
4 citations

Abstract

3D Gaussian Splatting (3D-GS) has recently attracted great attention with real-time and photo-realistic renderings. This technique typically takes perspective images as input and optimizes a set of 3D elliptical Gaussians by splatting them onto the image planes, resulting in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$2 D$</tex> Gaussians. However, applying 3D-GS to panoramic inputs presents challenges in effectively modeling the projection onto the spherical surface of 360° images using 2D Gaussians. In practical applications, input panoramas are often sparse, leading to unreliable initialization of 3D Gaussians and subsequent degradation of 3D-GS quality. In addition, due to the under-constrained geometry of texture-less planes (e.g., walls and floors), 3D-GS struggles to model these flat regions with elliptical Gaussians, resulting in significant floaters in novel views. To address these issues, we propose 360-GS, a novel layout-guided 360° Gaussian splatting for a limited set of panoramic inputs. Instead of splatting 3D Gaussians directly onto the spherical surface, 360-GS projects them onto the tangent plane of the unit sphere and then maps them to the spherical projections.

Nanjing University (CN)
Openalex Percentile: Top 1%
Computer Graphics and Visualization Techniques
14.16
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