14 citations · 17 across the 8 of their papers we have counts for
5 papers · 1 filter
From Restoration to Reconstruction: Rethinking 3D Gaussian Splatting for Underwater Scenes
Guoxi Huang, Haoran Wang, Zipeng Qi +3
Underwater image degradation poses significant challenges for 3D reconstruction, where simplified physical models often fail in complex scenes. We propose \textbf{R-Splatting}, a u…
Semantic-guided Gaussian Splatting for High-Fidelity Underwater Scene Reconstruction
Zhuodong Jiang, Haoran Wang, Guoxi Huang +2
Accurate 3D reconstruction in degraded imaging conditions remains a key challenge in photogrammetry and neural rendering. In underwater environments, spatially varying visibility c…
RUSplatting: Robust 3D Gaussian Splatting for Sparse-View Underwater Scene Reconstruction
Zhuodong Jiang, Haoran Wang, Guoxi Huang +2
Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aquatic environments. This paper p…
Visual enhancement and 3D representation for underwater scenes: a review
Guoxi Huang, Haoran Wang, Brett Seymour +4
Underwater visual enhancement (UVE) and underwater 3D reconstruction pose significant challenges in computer vision and AI-based tasks due to complex imaging conditions in aquatic…
LLGS: Unsupervised Gaussian Splatting for Image Enhancement and Reconstruction in Pure Dark Environment
Haoran Wang, Jingwei Huang, Lu Yang +3
3D Gaussian Splatting has shown remarkable capabilities in novel view rendering tasks and exhibits significant potential for multi-view optimization.However, the original 3D Gaussi…