SGSS: Streaming 6-DoF Navigation of Gaussian Splat Scenes

3D Gaussian Splatting (3DGS) is an emerging approach for training and representing real-world 3D scenes. Due to its photorealistic novel view synthesis and fast rendering speed (e.g., over 100 FPS), it has the potential to transform how scenes that can be explored in 6 degrees-of-freedom (6-DoF) are represented. However, a limiting factor of 3DGS is its large size, which requires high network bandwidth for streaming reconstructed real-world 3D scenes.

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Publication Details

Published
2025-03-26
DOI
https://doi.org/10.1145/3712676.3714437
Citations
3
Primary Topic
Advanced Vision and Imaging
Type
article
Field-Weighted Citation Impact
3.83

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article

SGSS: Streaming 6-DoF Navigation of Gaussian Splat Scenes

M.T. Liu, Mufeng Zhu, Cunxi Yu, Cheng-Hsin Hsu et al.
3 citations
Advanced Vision and Imaging
3.83
article

SGSS: Streaming 6-DoF Navigation of Gaussian Splat Scenes

M.T. Liu, Mufeng Zhu, Cunxi Yu, Cheng-Hsin Hsu, Yao Liu
article en
3 citations

Abstract

3D Gaussian Splatting (3DGS) is an emerging approach for training and representing real-world 3D scenes. Due to its photorealistic novel view synthesis and fast rendering speed (e.g., over 100 FPS), it has the potential to transform how scenes that can be explored in 6 degrees-of-freedom (6-DoF) are represented. However, a limiting factor of 3DGS is its large size, which requires high network bandwidth for streaming reconstructed real-world 3D scenes.

Rutgers, The State University of New Jersey (US), National Tsing Hua University (TW), University of Maryland, College Park (US)
National Science Foundation
Openalex Percentile: Top 7%
Advanced Vision and Imaging
3.83
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