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As 3D Gaussian Splatting (3DGS) provides fast and high-quality novel view synthesis, it is a natural extension to deform a canonical 3DGS to multiple frames for representing a dynamic scene. However, previous works fail to accurately…

Computer Vision and Pattern Recognition · Computer Science 2024-07-29 Jeongmin Bae , Seoha Kim , Youngsik Yun , Hahyun Lee , Gun Bang , Youngjung Uh

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Otto Seiskari , Jerry Ylilammi , Valtteri Kaatrasalo , Pekka Rantalankila , Matias Turkulainen , Juho Kannala , Esa Rahtu , Arno Solin

Reconstructing dynamic 3D scenes from monocular video remains fundamentally challenging due to the need to jointly infer motion, structure, and appearance from limited observations. Existing dynamic scene reconstruction methods based on…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Jiahui Li , Shengeng Tang , Jingxuan He , Gang Huang , Zhangye Wang , Yantao Pan , Lechao Cheng

4D Gaussian Splatting (4DGS) has recently emerged as a promising technique for capturing complex dynamic 3D scenes with high fidelity. It utilizes a 4D Gaussian representation and a GPU-friendly rasterizer, enabling rapid rendering speeds.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xinjie Zhang , Zhening Liu , Yifan Zhang , Xingtong Ge , Dailan He , Tongda Xu , Yan Wang , Zehong Lin , Shuicheng Yan , Jun Zhang

Three-dimensional reconstruction in scenes with extreme depth variations remains challenging due to inconsistent supervisory signals between near-field and far-field regions. Existing methods fail to simultaneously address inaccurate depth…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Yu Deng , Baozhu Zhao , Junyan Su , Xiaohan Zhang , Qi Liu

Novel view synthesis has been greatly enhanced by the development of radiance field methods. The introduction of 3D Gaussian Splatting (3DGS) has effectively addressed key challenges, such as long training times and slow rendering speeds,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Gopi Raju Matta , Reddypalli Trisha , Kaushik Mitra

We present ViewSplat, a view-adaptive 3D Gaussian splatting network for novel view synthesis from unposed images. While recent feed-forward 3D Gaussian splatting has significantly accelerated 3D scene reconstruction by bypassing per-scene…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Moonyeon Jeong , Seunggi Min , Suhyeon Lee , Hongje Seong

This paper investigates an open research challenge of reconstructing high-quality, large 3D open scenes from images. It is observed existing methods have various limitations, such as requiring precise camera poses for input and dense…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Chong Cheng , Gaochao Song , Yiyang Yao , Qinzheng Zhou , Gangjian Zhang , Hao Wang

Photorealistic 3D reconstruction of street scenes is a critical technique for developing real-world simulators for autonomous driving. Despite the efficacy of Neural Radiance Fields (NeRF) for driving scenes, 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Nan Huang , Xiaobao Wei , Wenzhao Zheng , Pengju An , Ming Lu , Wei Zhan , Masayoshi Tomizuka , Kurt Keutzer , Shanghang Zhang

Radiance field methods represent the state of the art in reconstructing complex scenes from multi-view photos. However, these reconstructions often suffer from one or both of the following limitations: First, they typically represent scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Chao Wang , Krzysztof Wolski , Bernhard Kerbl , Ana Serrano , Mojtaba Bemana , Hans-Peter Seidel , Karol Myszkowski , Thomas Leimkühler

We introduce FLAG-4D, a novel framework for generating novel views of dynamic scenes by reconstructing how 3D Gaussian primitives evolve through space and time. Existing methods typically rely on a single Multilayer Perceptron (MLP) to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Guan Yuan Tan , Ngoc Tuan Vu , Arghya Pal , Sailaja Rajanala , Raphael Phan C. -W. , Mettu Srinivas , Chee-Ming Ting

Recently, 3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis results, while allowing the rendering of high-resolution images in real-time. However, leveraging 3D Gaussians for surface reconstruction poses…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Zehao Yu , Torsten Sattler , Andreas Geiger

Recent works in volume rendering, \textit{e.g.} NeRF and 3D Gaussian Splatting (3DGS), significantly advance the rendering quality and efficiency with the help of the learned implicit neural radiance field or 3D Gaussians. Rendering on top…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Xiaobiao Du , Yida Wang , Xin Yu

The recent advent of 3D Gaussian Splatting (3DGS) has revolutionized the 3D scene reconstruction space enabling high-fidelity novel view synthesis in real-time. However, with the exception of RawNeRF, all prior 3DGS and NeRF-based methods…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Shreyas Singh , Aryan Garg , Kaushik Mitra

Although 3D Gaussian Splatting (3D-GS) achieves efficient rendering for novel view synthesis, extending it to dynamic scenes still results in substantial memory overhead from replicating Gaussians across frames. To address this challenge,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chun-Tin Wu , Jun-Cheng Chen

Recently, Gaussian Splatting has sparked a new trend in the field of computer vision. Apart from novel view synthesis, it has also been extended to the area of multi-view reconstruction. The latest methods facilitate complete, detailed…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Han Huang , Yulun Wu , Chao Deng , Ge Gao , Ming Gu , Yu-Shen Liu

Free-Viewpoint Video (FVV) reconstruction enables photorealistic and interactive 3D scene visualization; however, real-time streaming is often bottlenecked by sparse-view inputs, prohibitive training costs, and bandwidth constraints. While…

Graphics · Computer Science 2026-01-27 Xinhui Liu , Can Wang , Lei Liu , Zhenghao Chen , Wei Jiang , Wei Wang , Dong Xu

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis. However, existing methods struggle to adaptively optimize the distribution of Gaussian primitives based on scene characteristics, making it…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Hongbi Zhou , Zhangkai Ni

Reconstructing deformable endoscopic tissues is crucial for achieving robot-assisted surgery. However, 3D Gaussian Splatting-based approaches encounter challenges in achieving consistent tissue surface reconstruction, while existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yangsen Chen , Hao Wang
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