3D Gaussian Splatting for Enhanced Documentation of Cultural Artifacts

Abstract. 3D Gaussian splatting has shown promise for high-fidelity 3D modeling in cultural heritage documentation. However, applying 3DGS to cultural artifacts faces challenges, including image alignment errors in dynamic capture environments and background interference from scene-level reconstruction. We propose an optimized 3DGS framework tailored for artifact modeling, introducing two key innovations: (1) COLMAP-free for robust image alignment under non-static conditions, and (2) implementing targeted isolation to separate artifacts from extraneous backgrounds. Our approach enhances reconstruction quality, preserving intricate geometric details and critical textures for cultural artifacts. Comprehensive evaluations against traditional photogrammetry and standard 3DGS demonstrate superior performance in accuracy and visual fidelity. Through enhanced 3D Gaussian splatting, the proposed method achieves precise 3D documentation of cultural artifacts, enabling diverse digital applications.

Authors

Institutions

Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2025-09-23
DOI
https://doi.org/10.5194/isprs-annals-x-m-2-2025-215-2025
Primary Topic
Image Processing and 3D Reconstruction
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

3D Gaussian Splatting for Enhanced Documentation of Cultural Artifacts

Jongwon Choi, Jungmin Lee, Ji‐Hyun Min, So-Won Park
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Image Processing and 3D Reconstruction
article

3D Gaussian Splatting for Enhanced Documentation of Cultural Artifacts

Jongwon Choi, Jungmin Lee, Ji‐Hyun Min, So-Won Park
article en

Abstract

Abstract. 3D Gaussian splatting has shown promise for high-fidelity 3D modeling in cultural heritage documentation. However, applying 3DGS to cultural artifacts faces challenges, including image alignment errors in dynamic capture environments and background interference from scene-level reconstruction. We propose an optimized 3DGS framework tailored for artifact modeling, introducing two key innovations: (1) COLMAP-free for robust image alignment under non-static conditions, and (2) implementing targeted isolation to separate artifacts from extraneous backgrounds. Our approach enhances reconstruction quality, preserving intricate geometric details and critical textures for cultural artifacts. Comprehensive evaluations against traditional photogrammetry and standard 3DGS demonstrate superior performance in accuracy and visual fidelity. Through enhanced 3D Gaussian splatting, the proposed method achieves precise 3D documentation of cultural artifacts, enabling diverse digital applications.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. X-M-2-2025
National Research Institute of Cultural Heritage (KR), Chung-Ang University (KR)
Chung-Ang University, Ministry of Culture, Sports and Tourism, Korea Creative Content Agency, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion
Openalex Percentile: Top 74%
Image Processing and 3D Reconstruction
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.