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The underwater 3D scene reconstruction is a challenging, yet interesting problem with applications ranging from naval robots to VR experiences. The problem was successfully tackled by fully volumetric NeRF-based methods which can model both…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Huapeng Li , Wenxuan Song , Tianao Xu , Alexandre Elsig , Jonas Kulhanek

In underwater images, most useful features are occluded by water. The extent of the occlusion depends on imaging geometry and can vary even across a sequence of burst images. As a result, 3D reconstruction methods robust on in-air scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Nir Mualem , Roy Amoyal , Oren Freifeld , Derya Akkaynak

Underwater 3D reconstruction and appearance restoration are hindered by the complex optical properties of water, such as wavelength-dependent attenuation and scattering. Existing Neural Radiance Fields (NeRF)-based methods struggle with…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Xinrui Zhang , Yufeng Wang , Shuangkang Fang , Zesheng Wang , Dacheng Qi , Wenrui Ding

Real-time 3D reconstruction of surgical scenes plays a vital role in computer-assisted surgery, holding a promise to enhance surgeons' visibility. Recent advancements in 3D Gaussian Splatting (3DGS) have shown great potential for real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Jiaxin Guo , Jiangliu Wang , Di Kang , Wenzhen Dong , Wenting Wang , Yun-hui Liu

We introduce SeaSplat, a method to enable real-time rendering of underwater scenes leveraging recent advances in 3D radiance fields. Underwater scenes are challenging visual environments, as rendering through a medium such as water…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Daniel Yang , John J. Leonard , Yogesh Girdhar

3D Gaussian Splatting is a powerful visual representation, providing high-quality and efficient 3D scene reconstruction, but it is crucially dependent on accurate camera poses typically obtained from computationally intensive processes like…

Robotics · Computer Science 2026-04-15 Daniel Yang , Jungseok Hong , John J. Leonard , Yogesh Girdhar

Accurate 3D reconstruction in degraded imaging conditions remains a key challenge in photogrammetry and neural rendering. In underwater environments, spatially varying visibility caused by scattering, attenuation, and sparse observations…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

Underwater 3D scene reconstruction faces severe challenges from light absorption, scattering, and turbidity, which degrade geometry and color fidelity in traditional methods like Neural Radiance Fields (NeRF). While NeRF extensions such as…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Wenpeng Xing , Jie Chen , Zaifeng Yang , Changting Lin , Jianfeng Dong , Chaochao Chen , Xun Zhou , Meng Han

Underwater scene reconstruction is essential for immersive exploration of aquatic environments, yet remains challenging due to complex participating-media effects such as absorption and scattering, as well as the limited field of view (FoV)…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jiangbei Hu , Weichao Song , Shibo Yu , Mohan Wang , Zihan Yi , Rui Wu , Mingkang Xiang , Na Lei , Shengfa Wang , Zhongxuan Luo , Ying He

Reconstructing realistic underwater scenes from underwater video remains a meaningful yet challenging task in the multimedia domain. The inherent spatiotemporal degradations in underwater imaging, including caustics, flickering,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Shaohua Liu , Ning Gao , Zuoya Gu , Hongkun Dou , Yue Deng , Hongjue Li

3D Gaussian Splatting (3DGS) has emerged as a promising approach for 3D scene representation, offering a reduction in computational overhead compared to Neural Radiance Fields (NeRF). However, 3DGS is susceptible to high-frequency artifacts…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Shen Chen , Jiale Zhou , Lei Li

High-resolution remote sensing images (RSIs) are crucial for Earth observation applications, yet acquiring them is often limited by sensor constraints and costs. In recent years, generative super-resolution (SR) methods, particularly…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Jiangwei Mo , Xi Lu , Hanlin Wu

Reconstructing high-quality 3D models from sparse 2D images has garnered significant attention in computer vision. Recently, 3D Gaussian Splatting (3DGS) has gained prominence due to its explicit representation with efficient training speed…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Keng-Wei Chang , Zi-Ming Wang , Shang-Hong Lai

High-fidelity reconstruction of surgical scene is a fundamentally crucial task to support many applications, such as intra-operative navigation and surgical education. However, most existing methods assume the ideal surgical scenarios -…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Qian Li , Shuojue Yang , Daiyun Shen , Jimmy Bok Yan So , Jing Qin , Yueming Jin

Accurate 3D reconstruction of dynamic surgical scenes from endoscopic video is essential for robotic-assisted surgery. While recent 3D Gaussian Splatting methods have shown promise in achieving high-quality reconstructions with fast…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jialei Chen , Xin Zhang , Mobarakol Islam , Francisco Vasconcelos , Danail Stoyanov , Daniel S. Elson , Baoru Huang

Dynamic scene reconstruction has garnered significant attention in recent years due to its capabilities in high-quality and real-time rendering. Among various methodologies, constructing a 4D spatial-temporal representation, such as 4D-GS,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Weiwei Cai , Weicai Ye , Peng Ye , Tong He , Tao Chen

Standard 3D Gaussian Splatting (3DGS) relies on known or pre-computed camera poses and a sparse point cloud, obtained from structure-from-motion (SfM) preprocessing, to initialize and grow 3D Gaussians. We propose a novel SfM-Free 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Bo Ji , Angela Yao

Representing underwater 3D scenes is a valuable yet complex task, as attenuation and scattering effects during underwater imaging significantly couple the information of the objects and the water. This coupling presents a significant…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Shaohua Liu , Junzhe Lu , Zuoya Gu , Jiajun Li , Yue Deng

3D Gaussian splatting (3DGS) offers the capability to achieve real-time high quality 3D scene rendering. However, 3DGS assumes that the scene is in a clear medium environment and struggles to generate satisfactory representations in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Haoran Wang , Nantheera Anantrasirichai , Fan Zhang , David Bull

Water caustics are commonly observed in seafloor imaging data from shallow-water areas. Traditional methods that remove caustic patterns from images often rely on 2D filtering or pre-training on an annotated dataset, hindering the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Tianyi Zhang , Weiming Zhi , Kaining Huang , Joshua Mangelson , Corina Barbalata , Matthew Johnson-Roberson
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