High-Fidelity Seafloor 3D Reconstruction Based on Cross-dimensional Gaussian Normal Transition Field

ZHAO Ximan; CHU Xuanhe; CHEN Han; LIU Siyuan

doi:10.11993/j.issn.2096-3920.2025-0167

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ZHAO Ximan, CHU Xuanhe, CHEN Han, LIU Siyuan. High-Fidelity Seafloor 3D Reconstruction Based on Cross-dimensional Gaussian Normal Transition Field[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0167

Citation:

ZHAO Ximan, CHU Xuanhe, CHEN Han, LIU Siyuan. High-Fidelity Seafloor 3D Reconstruction Based on Cross-dimensional Gaussian Normal Transition Field[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0167

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High-Fidelity Seafloor 3D Reconstruction Based on Cross-dimensional Gaussian Normal Transition Field

doi: 10.11993/j.issn.2096-3920.2025-0167

Marine Engineering College, Dalian Maritime University, Dalian 116026, China

Received Date: 2025-12-16
Accepted Date: 2026-02-09
Rev Recd Date: 2026-02-04

Available Online: 2026-07-14

Abstract

Abstract

The demand for high-fidelity scene reconstruction of the seafloor is growing in fields such as marine scientific surveying and underwater environmental exploration. As an advanced explicit scene representation method, 3D Gaussian Splatting shows significant application potential in scene reconstruction and novel view synthesis. However, influenced by factors such as blurring effects in underwater medium, the results often exhibit defects like medium artifacts and structural distortion, severely limiting their applicability in complex underwater environments. To address these challenges, we propose a high-fidelity seafloor scene reconstruction based on cross-dimensional Gaussian normal transition field. First, we establish a cross-dimensional and normal transition system for Gaussian primitives, enhancing its capability for detailed geometric modeling of complex structures. Second, we introduce a Gaussian opacity-weighted filtering model to suppress reconstruction artifacts caused by medium blurring effects. Finally, experimental results across multiple underwater scenes demonstrate our method's capability for efficient scene reconstruction and novel view synthesis in underwater environments.
- underwater scene reconstruction,
- novel view synthesis,
- 3d gaussian splatting,
- underwater medium imaging,
- complex structure modeling

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References(19)

References

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