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We introduce an image upscaling technique tailored for 3D Gaussian Splatting (3DGS) on lightweight GPUs. Compared to 3DGS, it achieves significantly higher rendering speeds and reduces artifacts commonly observed in 3DGS reconstructions.…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Simon Niedermayr , Christoph Neuhauser Rüdiger Westermann

3D Gaussian Splatting (3DGS) has revolutionized 3D scene reconstruction, which effectively balances rendering quality, efficiency, and speed. However, existing 3DGS approaches usually generate plausible outputs and face significant…

Graphics · Computer Science 2025-07-22 Beizhen Zhao , Yifan Zhou , Sicheng Yu , Zijian Wang , Hao Wang

Neural rendering methods have significantly advanced photo-realistic 3D scene rendering in various academic and industrial applications. The recent 3D Gaussian Splatting method has achieved the state-of-the-art rendering quality and speed…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Tao Lu , Mulin Yu , Linning Xu , Yuanbo Xiangli , Limin Wang , Dahua Lin , Bo Dai

The dominant 3D Gaussian splatting (3DGS) acceleration methods fail to properly regulate the number of Gaussians during training, causing redundant computational time overhead. In this paper, we propose FastGS, a novel, simple, and general…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shiwei Ren , Tianci Wen , Yongchun Fang , Biao Lu

Open-vocabulary 3D scene understanding presents a significant challenge in computer vision, with wide-ranging applications in embodied agents and augmented reality systems. Existing methods adopt neurel rendering methods as 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Jun Guo , Xiaojian Ma , Yue Fan , Huaping Liu , Qing Li

Feed-forward 3D Gaussian Splatting (3DGS) has emerged as a highly effective solution for novel view synthesis. Existing methods predominantly rely on a \emph{pixel-aligned} Gaussian prediction paradigm, where each 2D pixel is mapped to a 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Weijie Wang , Yeqing Chen , Zeyu Zhang , Hengyu Liu , Haoxiao Wang , Zhiyuan Feng , Wenkang Qin , Feng Chen , Zheng Zhu , Donny Y. Chen , Bohan Zhuang

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 (3DGS) has emerged as a leading approach for high-quality novel view synthesis, with numerous variants extending its applicability to a broad spectrum of 3D and 4D scene reconstruction tasks. Despite its success, the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yiming Wang , Shaofei Wang , Marko Mihajlovic , Siyu Tang

Modeling and understanding the 3D world is crucial for various applications, from augmented reality to robotic navigation. Recent advancements based on 3D Gaussian Splatting have integrated semantic information from multi-view images into…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Xingrui Wang , Cuiling Lan , Hanxin Zhu , Zhibo Chen , Yan Lu

3D Gaussian Splatting (3D-GS) technique couples 3D Gaussian primitives with differentiable rasterization to achieve high-quality novel view synthesis results while providing advanced real-time rendering performance. However, due to the flaw…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Zongxin Ye , Wenyu Li , Sidun Liu , Peng Qiao , Yong Dou

3D Gaussian Splatting (3DGS) has become a leading representation for high-fidelity 3D assets, yet protecting these assets via digital watermarking remains an open challenge. Existing 3DGS watermarking methods are robust only to classical…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Longjie Zhao , Ziming Hong , Zhenyang Ren , Runnan Chen , Mingming Gong , Tongliang Liu

Recently, 3D Gaussian splatting has gained attention for its capability to generate high-fidelity rendering results. At the same time, most applications such as games, animation, and AR/VR use mesh-based representations to represent and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Jaehoon Choi , Yonghan Lee , Hyungtae Lee , Heesung Kwon , Dinesh Manocha

Dynamic extensions of 3D Gaussian Splatting (3DGS) achieve high-quality reconstructions through neural motion fields, but per-Gaussian neural inference makes these models computationally expensive. Building on DeformableGS, we introduce…

Graphics · Computer Science 2026-03-31 Allen Tu , Haiyang Ying , Alex Hanson , Yonghan Lee , Tom Goldstein , Matthias Zwicker

In the context of novel view synthesis, 3D Gaussian Splatting (3DGS) has recently emerged as an efficient and competitive counterpart to Neural Radiance Field (NeRF), enabling high-fidelity photorealistic rendering in real time. Beyond…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Shuting He , Peilin Ji , Yitong Yang , Changshuo Wang , Jiayi Ji , Yinglin Wang , Henghui Ding

3D Gaussian Splatting (3DGS) has garnered significant attention due to its superior scene representation fidelity and real-time rendering performance, especially for dynamic 3D scene reconstruction (\textit{i.e.}, 4D reconstruction).…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Henan Wang , Hanxin Zhu , Xinliang Gong , Tianyu He , Xin Li , Zhibo Chen

3D Gaussian Splatting (3DGS) has recently created impressive 3D assets for various applications. However, considering security, capacity, invisibility, and training efficiency, the copyright of 3DGS assets is not well protected as existing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Zixuan Chen , Guangcong Wang , Jiahao Zhu , Jianhuang Lai , Xiaohua Xie

3D Gaussian Splatting (3DGS) has become horsepower in high-quality, real-time rendering for novel view synthesis of 3D scenes. However, existing methods focus primarily on geometric and appearance modeling, lacking deeper scene…

Graphics · Computer Science 2025-07-01 Minchao Jiang , Shunyu Jia , Jiaming Gu , Xiaoyuan Lu , Guangming Zhu , Anqi Dong , Liang Zhang

Gaussian Splatting (GS) has recently marked a significant advancement in 3D reconstruction, delivering both rapid rendering and high-quality results. However, existing 3DGS methods pose challenges in understanding underlying 3D semantics,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yuyang Zhang , Baao Xie , Hu Zhu , Qi Wang , Huanting Guo , Xin Jin , Wenjun Zeng

Recent works demonstrate the advantages of hardware rasterization for 3D Gaussian Splatting (3DGS) in forward-pass rendering through fast GPU-optimized graphics and fixed memory footprint. However, extending these benefits to backward-pass…

Graphics · Computer Science 2025-08-14 Yitian Yuan , Qianyue He

3D Gaussian Splatting (3DGS) has become one of the most influential works in the past year. Due to its efficient and high-quality novel view synthesis capabilities, it has been widely adopted in many research fields and applications.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Glenn Grubert , Florian Barthel , Anna Hilsmann , Peter Eisert
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