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Current 4D Gaussian frameworks for dynamic scene reconstruction deliver impressive visual fidelity and rendering speed, however, the inherent trade-off between storage costs and the ability to characterize complex physical motions…

Graphics · Computer Science 2025-07-11 Wei Yao , Shuzhao Xie , Letian Li , Weixiang Zhang , Zhixin Lai , Shiqi Dai , Ke Zhang , Zhi Wang

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

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

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

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

Existing 4D Gaussian Splatting methods rely on per-Gaussian deformation from a canonical space to target frames, which overlooks redundancy among adjacent Gaussian primitives and results in suboptimal performance. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 He Huang , Qi Yang , Mufan Liu , Yiling Xu , Zhu Li

Dynamic and static components in scenes often exhibit distinct properties, yet most 4D reconstruction methods treat them indiscriminately, leading to suboptimal performance in both cases. This work introduces SDD-4DGS, the first framework…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Dai Sun , Huhao Guan , Kun Zhang , Xike Xie , S. Kevin Zhou

Recent progress in pre-trained diffusion models and 3D generation have spurred interest in 4D content creation. However, achieving high-fidelity 4D generation with spatial-temporal consistency remains a challenge. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Yifei Zeng , Yanqin Jiang , Siyu Zhu , Yuanxun Lu , Youtian Lin , Hao Zhu , Weiming Hu , Xun Cao , Yao Yao

Existing dynamic scene reconstruction methods based on Gaussian Splatting enable real-time rendering and generate realistic images. However, adjusting the camera's focal length or the distance between Gaussian primitives and the camera to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Zilong Chen , Huan-ang Gao , Delin Qu , Haohan Chi , Hao Tang , Kai Zhang , Hao Zhao

Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee. To achieve real-time dynamic scene rendering while also…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Guanjun Wu , Taoran Yi , Jiemin Fang , Lingxi Xie , Xiaopeng Zhang , Wei Wei , Wenyu Liu , Qi Tian , Xinggang Wang

This paper addresses the problem of dynamic scene surface reconstruction using Gaussian Splatting (GS), aiming to recover temporally consistent geometry. While existing GS-based dynamic surface reconstruction methods can yield superior…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Renjie Wu , Hongdong Li , Jose M. Alvarez , Miaomiao Liu

Reconstructing dynamic scenes from video sequences is a highly promising task in the multimedia domain. While previous methods have made progress, they often struggle with slow rendering and managing temporal complexities such as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jinbo Yan , Rui Peng , Luyang Tang , Ronggang Wang

Remarkable advances in recent 2D image and 3D shape generation have induced a significant focus on dynamic 4D content generation. However, previous 4D generation methods commonly struggle to maintain spatial-temporal consistency and adapt…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Mengmeng Liu , Jiuming Liu , Yunpeng Zhang , Jiangtao Li , Michael Ying Yang , Francesco Nex , Hao Cheng

Dynamic 4D Gaussian Splatting (4DGS) effectively extends the high-speed rendering capabilities of 3D Gaussian Splatting (3DGS) to represent volumetric videos. However, the large number of Gaussians, substantial temporal redundancies, and…

Graphics · Computer Science 2026-01-14 Hyeongmin Lee , Kyungjune Baek

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

Recently, Gaussian splatting has received more and more attention in the field of static scene rendering. Due to the low computational overhead and inherent flexibility of explicit representations, plane-based explicit methods are popular…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Jiawei Xu , Zexin Fan , Jian Yang , Jin Xie

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

3D Gaussian Splatting has demonstrated remarkable real-time rendering capabilities and superior visual quality in novel view synthesis for static scenes. Building upon these advantages, researchers have progressively extended 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Han Jiao , Jiakai Sun , Lei Zhao , Zhanjie Zhang , Wei Xing , Huaizhong Lin

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

Dynamic scene reconstruction with Gaussian Splatting has enabled efficient streaming for real-time rendering and free-viewpoint video. However, most pipelines rely on fixed anchor selection such as Farthest Point Sampling (FPS), typically…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Ashim Dahal , Rabab Abdelfattah , Nick Rahimi
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