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<p>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: <a href="https://github.com/ruigong335-creator/A-Survey-on-Aerial-Scene-Editing">https://github.com/ruigong335-creator/A-Survey-on-Aerial-Scene-Editing</a>.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月9日

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  • Rui Gong,
  • Jiguang Zhang,
  • Yujia Pang,
  • Yixuan Wang,
  • Xiaopeng Zhang,
  • Weiliang Meng,
  • Peng Zhou

摘要

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.