WaterClear-GS introduces a physics-informed Gaussian splatting method tailored for underwater 3D reconstruction and appearance restoration. It models underwater degradation as intrinsic Gaussian attributes and employs a dual-branch optimization that separates clean appearance from degradation while preserving photometric consistency. The approach incorporates depth-guided geometry regularization, perception-driven supervision, exposure constraints, adaptive regularization, and spectral regularization, achieving strong novel view synthesis and image restoration performance at over 160 FPS.
By Xinrui Zhang, Yufeng Wang, Zesheng Wang, Dacheng Qi, Wenrui Ding, Shuangkang Fang
Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-quality 3D annotations. Pioneering methods rely on massive dense annotations that are impractical in underwater settings.
RUSplatting introduces a robust 3D Gaussian splatting framework for reconstructing high‑fidelity underwater scenes from sparse views. The method decouples RGB learning guided by underwater attenuation physics, employs a novel adaptive weighting scheme for frame interpolation, and adds a loss function that reduces noise while preserving edges. Experiments on the newly released Submerged3D dataset show PSNR gains up to 1.90 dB over state‑of‑the‑art methods, improving both visual quality and geometric accuracy for deep‑sea rendering.
By Zhuodong Jiang, Haoran Wang, Guoxi Huang, Brett Seymour, Nantheera Anantrasirichai
Reconstructing photorealistic scenes in unconstrained underwater environments remains challenging due to severe media-induced light scattering and unpredictable dynamic objects. Recent feed-forward vi...
OceanXL is a new framework that applies 3D Gaussian Splatting to large-scale underwater scenes by partitioning them into spatially coherent blocks and using adaptive pruning to remove redundant primitives. This divide‑and‑conquer approach improves training efficiency and rendering performance while maintaining global geometric consistency. The authors also release a large underwater dataset and demonstrate that OceanXL achieves favorable scalability, compactness, and efficiency compared to existing baselines, with competitive quality on smaller datasets and smaller model sizes than other underwater methods.
By Haoran Wang, Shaoyu Cai, Adrian Azzarelli, Zhuodong Jiang, Guoxi Huang, Eng Tat Khoo, Brett Seymour, Fan Zhang, David Bull, Nantheera Anantrasirichai
arXiv:2608.22906v1 Announce Type: new
Abstract: Recent monocular 3D Gaussian Splatting (3DGS) streaming reconstruction methods have achieved impressive performance by balancing reconstruction quality...
By Yingxiang Xu, Kerui Ren, Wenqi Guo, Changjian Jiang, Tao Lu, Linning Xu, Mulin Yu
Reliable feedforward underwater 3D reconstruction remains challenging due to severe light attenuation and backscattering, which degrade visual quality and disrupt feature consistency across views, leading to inaccurate multi-view geometry. To address this issue, we propose WAT3R, a feed-forward framework for reconstructing 3D scenes directly from underwater images.
Recent monocular 3D Gaussian Splatting (3DGS) streaming reconstruction methods have achieved impressive performance by balancing reconstruction quality and efficiency. However, extending these framewo...
arXiv:2608.22888v1 Announce Type: new
Abstract: Reconstructing photorealistic scenes in unconstrained underwater environments remains challenging due to severe media-induced light scattering and unpr...
By Xiaopeng Guo, Wai Chung Tse, Yipeng Zhu, Hanwen Zhang, Huajian Huang, Sai-Kit Yeung
arXiv:2609.18737v1 Announce Type: new
Abstract: Underwater 3D reconstruction supports applications ranging from marine ecosystem monitoring and subsea inspection to underwater archaeology, education,...
By Harvey Caldeira, Haoran Wang, Guoxi Huang, Shaoyu Cai, Rachel Fu, Nantheera Anantrasirichai
AQUA-Net is a lightweight underwater image enhancement model that fuses spatial, frequency, and illumination information through a residual encoder‑decoder architecture with dual auxiliary branches. The frequency fusion encoder incorporates Fourier‑domain cues to preserve textures and details, while the illumination‑aware decoder applies adaptive exposure correction based on a learned illumination map. Experiments on benchmark datasets and a new high‑resolution Mediterranean Sea video set demonstrate that AQUA-Net achieves state‑of‑the‑art performance with fewer parameters, showing strong generalization and robustness for real‑world underwater imaging.
By Munsif Ali, Najmul Hassan, Lucia Ventura, Davide Di Bari, Simonepietro Canese, Jungpil Shin
The paper introduces an extension to the OceanSim underwater perception simulator, adding a Synthetic Data Generation pipeline that produces large, automatically labeled, photorealistic datasets with configurable scene and sensor settings. The authors evaluate this pipeline on a real-world sea urchin detection task, examining how different synthetic scene variations influence sim-to-real performance. They discuss the pipeline’s findings, limitations, and future directions for improving rendering fidelity, scene diversity, and sim-to-real generalization.
By Haoyu Ma, Onur Bagoren, Anja Sheppard, Elias Fandi, Ashrith Edukulla, Tanner Aslan, Natasha Sieh, Jingyu Song, Katherine A. Skinner