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Representing 3D scenes from multiview images is a core challenge in computer vision and graphics, which requires both precise rendering and accurate reconstruction. Recently, 3D Gaussian Splatting (3DGS) has garnered significant attention…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 You Shen , Zhipeng Zhang , Xinyang Li , Yansong Qu , Yu Lin , Shengchuan Zhang , Liujuan Cao

While 3D Gaussian Splatting (3DGS) excels in static scene modeling, its extension to dynamic scenes introduces significant challenges. Existing dynamic 3DGS methods suffer from either over-smoothing due to low-rank decomposition or feature…

Graphics · Computer Science 2025-08-08 Yifan Zhou , Beizhen Zhao , Pengcheng Wu , Hao Wang

3D Gaussian Splatting (3DGS) has emerged as a novel paradigm for 3D reconstruction from satellite imagery. However, in multi-temporal satellite images, prevalent shadows exhibit significant inconsistencies due to varying illumination…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Feng Luo , Hongbo Pan , Xiang Yang , Baoyu Jiang , Fengqing Liu , Tao Huang

3D Gaussian Splatting (GS) has emerged as a powerful representation for high-quality scene reconstruction, offering compelling rendering quality. However, the training process of GS often suffers from slow convergence due to inefficient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Binxiao Huang , Zhengwu Liu , Ngai Wong

3D Gaussian Splatting (3DGS) has shown its ability in rapid rendering and high-fidelity mapping. In this paper, we introduce LVI-GS, a tightly-coupled LiDAR-Visual-Inertial mapping framework with 3DGS, which leverages the complementary…

Robotics · Computer Science 2024-11-06 Huibin Zhao , Weipeng Guan , Peng Lu

3D Gaussian Splatting (3DGS) is a recent explicit 3D representation that has achieved high-quality reconstruction and real-time rendering of complex scenes. However, the rasterization pipeline still suffers from unnecessary overhead…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Xinzhe Wang , Ran Yi , Lizhuang Ma

Gaussian splatting (GS) for 3D reconstruction has become quite popular due to their fast training, inference speeds and high quality reconstruction. However, GS-based reconstructions generally consist of millions of Gaussians, which makes…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Anil Armagan , Albert Saà-Garriga , Bruno Manganelli , Mateusz Nowak , Mehmet Kerim Yucel

3D Gaussian Splatting (3DGS) has emerged as an efficient approach for achieving photorealistic rendering. Recent MLP-based variants further improve visual fidelity but introduce substantial decoding overhead during rendering. To alleviate…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Yuanyuan Gao , Yuning Gong , Yifei Liu , Li Jingfeng , Dingwen Zhang , Yanci Zhang , Dan Xu , Xiao Sun , Zhihang Zhong

This paper introduces LiGSM, a novel LiDAR-enhanced 3D Gaussian Splatting (3DGS) mapping framework that improves the accuracy and robustness of 3D scene mapping by integrating LiDAR data. LiGSM constructs joint loss from images and LiDAR…

Robotics · Computer Science 2025-03-10 Jian Shen , Huai Yu , Ji Wu , Wen Yang , Gui-Song Xia

Novel view synthesis has demonstrated impressive progress recently, with 3D Gaussian splatting (3DGS) offering efficient training time and photorealistic real-time rendering. However, reliance on Cartesian coordinates limits 3DGS's…

Graphics · Computer Science 2025-03-26 Xinpeng Liu , Zeyi Huang , Fumio Okura , Yasuyuki Matsushita

3D Gaussian Splatting (3DGS) is a promising technique for 3D reconstruction, offering efficient training and rendering speeds, making it suitable for real-time applications.However, current methods require highly controlled environments (no…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Sara Sabour , Lily Goli , George Kopanas , Mark Matthews , Dmitry Lagun , Leonidas Guibas , Alec Jacobson , David J. Fleet , Andrea Tagliasacchi

3D modeling of highly reflective objects remains challenging due to strong view-dependent appearances. While previous SDF-based methods can recover high-quality meshes, they are often time-consuming and tend to produce over-smoothed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jinguang Tong , Xuesong li , Fahira Afzal Maken , Sundaram Muthu , Lars Petersson , Chuong Nguyen , Hongdong Li

In this work, we present Fed3DGS, a scalable 3D reconstruction framework based on 3D Gaussian splatting (3DGS) with federated learning. Existing city-scale reconstruction methods typically adopt a centralized approach, which gathers all…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Teppei Suzuki

3D Gaussian Splatting SLAM has emerged as a widely used technique for high-fidelity mapping in spatial intelligence. However, existing methods often rely on a single representation scheme, which limits their performance in large-scale…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Wenkai Zhu , Xu Li , Qimin Xu , Benwu Wang , Kun Wei , Yiming Peng , Zihang Wang

3D Gaussian Splatting (3DGS) has recently emerged as a promising contender to Neural Radiance Fields (NeRF) in 3D scene reconstruction and real-time novel view synthesis. 3DGS outperforms NeRF in training and inference speed but has…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Bert Ramlot , Martijn Courteaux , Peter Lambert , Glenn Van Wallendael

3D Gaussian splatting video (3DGS) streaming has recently emerged as a research hotspot in both academia and industry, owing to its impressive ability to deliver immersive 3D video experiences. However, research in this area is still in its…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Han Gong , Qiyue Li , Jie Li , Zhi Liu

As generative models become increasingly capable of producing high-fidelity visual content, the demand for efficient, interpretable, and editable image representations has grown substantially. Recent advances in 2D Gaussian Splatting (2DGS)…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Hao Wang , Ashish Bastola , Chaoyi Zhou , Wenhui Zhu , Xiwen Chen , Xuanzhao Dong , Siyu Huang , Abolfazl Razi

3D Gaussian Splatting (3DGS) reconstructions are plagued by stubborn ``floater" artifacts that degrade their geometric and visual fidelity. We are the first to reveal the root cause: a fundamental conflict in the 3DGS optimization process…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Luchao Wang , Qian Ren , Kaimin Liao , Hua Wang , Zhi Chen , Yaohua Tang

Rapid, large-scale 3D reconstruction from multi-date satellite imagery is vital for environmental monitoring, urban planning, and disaster response, yet remains difficult due to illumination changes, sensor heterogeneity, and the cost of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Rong Fu , Jiekai Wu , Haiyun Wei , Xiaowen Ma , Shiyin Lin , Kangan Qian , Chuang Liu , Jianyuan Ni , Simon James Fong

3D head animation has seen major quality and runtime improvements over the last few years, particularly empowered by the advances in differentiable rendering and neural radiance fields. Real-time rendering is a highly desirable goal for…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Helisa Dhamo , Yinyu Nie , Arthur Moreau , Jifei Song , Richard Shaw , Yiren Zhou , Eduardo Pérez-Pellitero
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