EVSplitting: An Efficient and Visually Consistent Splitting Algorithm for 3D Gaussian Splatting

This paper presents EVSplitting, an efficient and visually consistent splitting algorithm for 3D Gaussian Splatting (3DGS). It is designed to make operating 3DGS as easy and effective as other 3D explicit representations, readily for industrial productions. The challenges of above target are: 1) The huge number and complex attributes of 3DGS make it tough to explicitly operate on 3DGS in a real-time and learning-free manner; 2) The visual effect of 3DGS is very difficult to maintain during explicit operations and 3) The anisotropism of Gaussian always leads to blurs and artifacts. As far as we know, no prior work can address these challenges well. In this work, we introduce a direct and efficient 3DGS splitting algorithm to solve them. Specifically, we formulate the 3DGS splitting as two minimization problems that aim to ensure visual consistency and reduce Gaussian overflow across boundary (splitting plane), respectively. Firstly, we impose conservations on the zero-, first- and second-order moments of the weighted Gaussian distribution to guarantee visual consistency. Secondly, we reduce the boundary overflow with a special constraint on the aforementioned conservations. With these conservations and constraints, we derive a closed-form solution for the 3DGS splitting problem. This yields an easy-to-implement, plug-and-play, efficient and fundamental tool, benefiting various downstream applications of 3DGS.

Authors

Institutions

Publication Details

Published
2024-12-03
DOI
https://doi.org/10.1145/3680528.3687592
Citations
6
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
3.79

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

EVSplitting: An Efficient and Visually Consistent Splitting Algorithm for 3D Gaussian Splatting

Ralph R. Martin, Hao-Xiang Chen, Shi‐Min Hu, Geng-Chen Cao et al.
6 citations
Computer Graphics and Visualization Techniques
3.79
article

EVSplitting: An Efficient and Visually Consistent Splitting Algorithm for 3D Gaussian Splatting

Ralph R. Martin, Hao-Xiang Chen, Shi‐Min Hu, Geng-Chen Cao, Tai‐Jiang Mu, Qi-Yuan Feng, Qun‐Ce Xu
article en
6 citations

Abstract

This paper presents EVSplitting, an efficient and visually consistent splitting algorithm for 3D Gaussian Splatting (3DGS). It is designed to make operating 3DGS as easy and effective as other 3D explicit representations, readily for industrial productions. The challenges of above target are: 1) The huge number and complex attributes of 3DGS make it tough to explicitly operate on 3DGS in a real-time and learning-free manner; 2) The visual effect of 3DGS is very difficult to maintain during explicit operations and 3) The anisotropism of Gaussian always leads to blurs and artifacts. As far as we know, no prior work can address these challenges well. In this work, we introduce a direct and efficient 3DGS splitting algorithm to solve them. Specifically, we formulate the 3DGS splitting as two minimization problems that aim to ensure visual consistency and reduce Gaussian overflow across boundary (splitting plane), respectively. Firstly, we impose conservations on the zero-, first- and second-order moments of the weighted Gaussian distribution to guarantee visual consistency. Secondly, we reduce the boundary overflow with a special constraint on the aforementioned conservations. With these conservations and constraints, we derive a closed-form solution for the 3DGS splitting problem. This yields an easy-to-implement, plug-and-play, efficient and fundamental tool, benefiting various downstream applications of 3DGS.

Cardiff University (GB), Tsinghua University (CN)
Tencent, National Natural Science Foundation of China, Tsinghua University, National Science and Technology Major Project
Climate action
Openalex Percentile: Top 4%
Computer Graphics and Visualization Techniques
3.79
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.