Implicit vs. explicit a comparative survey on NeRF and 3DGS for large-scale aerial scene editing

The proliferation of Unmanned Aerial Vehicles (UAVs) has significantly advanced large-scale 3D data acquisition, paving the way for Digital Twin applications. While Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) now enable exceptional photorealism, editing these vast neural representations remains a significant challenge. This survey systematically analyzes large-scale scene editing from UAV imagery, specifically focusing on the architectural dichotomy between implicit (NeRF) and explicit (3DGS) representations. We introduce novel taxonomies to deconstruct their core mechanisms and critically evaluate why explicit representations are currently emerging as the more viable path for interactive, city-scale manipulation. Furthermore, we identify key bottlenecks—such as handling oblique views and variable atmospheric conditions—and outline future research directions.A comprehensive and regularly updated collection of the surveyed papers and resources is available at our project website: https://github.com/ruigong335-creator/A-Survey-on-Aerial-Scene-Editing .

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Publication Details

Journal
Discover Computing
Published
2026-03-09
DOI
https://doi.org/10.1007/s10791-026-10029-9
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
0.00

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article

Implicit vs. explicit a comparative survey on NeRF and 3DGS for large-scale aerial scene editing

Y. Wang, Jiguang Zhang, Yu Pang, Rui Gong et al.
Discover Computing
3D Surveying and Cultural Heritage
article

Implicit vs. explicit a comparative survey on NeRF and 3DGS for large-scale aerial scene editing

Y. Wang, Jiguang Zhang, Yu Pang, Rui Gong, Xiaopeng Zhang, Peng Zhou, Weiliang Meng
article en

Abstract

The proliferation of Unmanned Aerial Vehicles (UAVs) has significantly advanced large-scale 3D data acquisition, paving the way for Digital Twin applications. While Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) now enable exceptional photorealism, editing these vast neural representations remains a significant challenge. This survey systematically analyzes large-scale scene editing from UAV imagery, specifically focusing on the architectural dichotomy between implicit (NeRF) and explicit (3DGS) representations. We introduce novel taxonomies to deconstruct their core mechanisms and critically evaluate why explicit representations are currently emerging as the more viable path for interactive, city-scale manipulation. Furthermore, we identify key bottlenecks—such as handling oblique views and variable atmospheric conditions—and outline future research directions.A comprehensive and regularly updated collection of the surveyed papers and resources is available at our project website: https://github.com/ruigong335-creator/A-Survey-on-Aerial-Scene-Editing .

Discover ComputingVol. 29(1)
Beijing Jiaotong University (CN), UNSW Sydney (AU), Zhejiang Institute of Communications (CN), Institute of Automation (CN)
National Natural Science Foundation of China, Beihang University, State Key Laboratory of Virtual Reality Technology and Systems
Sustainable cities and communities
Openalex Percentile: Top 37%
3D Surveying and Cultural Heritage
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Implicit vs. explicit a comparative survey on NeRF and 3DGS for large-scale aerial scene editing — Y. Wang, Jiguang Zhang, et al. · Discover Computing (2026) | TGRS Research Map | TGRS