GS-Share: Enabling High-fidelity Map Sharing with Incremental Gaussian Splatting
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
Constructing and sharing 3D maps is essential for many applications, including autonomous driving and augmented reality. Recently, 3D Gaussian splatting has emerged as a promising approach for accurate 3D reconstruction. However, a practical map-sharing system that features high-fidelity, continuous updates, and network efficiency remains elusive. To address these challenges, we introduce GS-Share, a photorealistic map-sharing system with a compact representation. The core of GS-Share includes anchor-based global map construction, virtual-image-based map enhancement, and incremental map update. We evaluate GS-Share against state-of-the-art methods, demonstrating that our system achieves higher fidelity, particularly for extrapolated views, with improvements of 11%, 22%, and 74% in PSNR, LPIPS, and Depth L1, respectively. Furthermore, GS-Share is significantly more compact, reducing map transmission overhead by 36%.
Description
CCS Concepts: Computing methodologies → Rendering; Shape modeling; Information systems → Data compression
@article{10.1111:cgf.70248,
journal = {Computer Graphics Forum},
title = {{GS-Share: Enabling High-fidelity Map Sharing with Incremental Gaussian Splatting}},
author = {Zhang, Xinran and Zhu, Hanqi and Duan, Yifan and Zhang, Yanyong},
year = {2025},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.70248}
}