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Related papers: MoDec-GS: Global-to-Local Motion Decomposition and…

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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

Dynamic novel view synthesis (NVS) is essential for creating immersive experiences. Existing approaches have advanced dynamic NVS by introducing 3D Gaussian Splatting (3DGS) with implicit deformation fields or indiscriminately assigned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Kaizhe Zhang , Yijie Zhou , Weizhan Zhang , Caixia Yan , Haipeng Du , yugui xie , Yu-Hui Wen , Yong-Jin Liu

Realistic reconstruction of dynamic 4D scenes from monocular videos is essential for understanding the physical world. Despite recent progress in neural rendering, existing methods often struggle to recover accurate 3D geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Haoran Zhou , Gim Hee Lee

Previous surface reconstruction methods either suffer from low geometric accuracy or lengthy training times when dealing with real-world complex dynamic scenes involving multi-person activities, and human-object interactions. To tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shuo Wang , Binbin Huang , Ruoyu Wang , Shenghua Gao

3D Gaussian Splatting (3DGS) has gained significant attention in streamable dynamic novel view synthesis (DNVS) for its photorealistic rendering capability and computational efficiency. Despite much progress in improving rendering quality…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Zhenyu Bao , Qing Li , Guibiao Liao , Zhongyuan Zhao , Kanglin Liu

Reconstructing deformable tissues from endoscopic videos is essential in many downstream surgical applications. However, existing methods suffer from slow rendering speed, greatly limiting their practical use. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Yifan Liu , Chenxin Li , Chen Yang , Yixuan Yuan

The reconstruction of dynamic 3D scenes using 3D Gaussian Splatting has shown significant promise. A key challenge, however, remains in modeling realistic motion, as most methods fail to align the motion of Gaussians with real-world…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Junoh Lee , Junmyeong Lee , Yeon-Ji Song , Inhwan Bae , Jisu Shin , Hae-Gon Jeon , Jin-Hwa Kim

3D Gaussian Splatting (3DGS) has gained significant attention due to its high-quality novel view rendering, motivating research to address real-world challenges. A critical issue is the camera motion blur caused by movement during exposure,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jungho Lee , Donghyeong Kim , Dogyoon Lee , Suhwan Cho , Minhyeok Lee , Wonjoon Lee , Taeoh Kim , Dongyoon Wee , Sangyoun Lee

3D reconstruction and simulation, although interrelated, have distinct objectives: reconstruction requires a flexible 3D representation that can adapt to diverse scenes, while simulation needs a structured representation to model motion…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Shaojie Ma , Yawei Luo , Wei Yang , Yi Yang

3D Gaussian Splatting, known for enabling high-quality static scene reconstruction with fast rendering, is increasingly being applied to multi-view dynamic scene reconstruction. A common strategy involves learning a deformation field to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Han Jiao , Jiakai Sun , Yexing Xu , Lei Zhao , Wei Xing , Huaizhong Lin

We present DeSiRe-GS, a self-supervised gaussian splatting representation, enabling effective static-dynamic decomposition and high-fidelity surface reconstruction in complex driving scenarios. Our approach employs a two-stage optimization…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Chensheng Peng , Chengwei Zhang , Yixiao Wang , Chenfeng Xu , Yichen Xie , Wenzhao Zheng , Kurt Keutzer , Masayoshi Tomizuka , Wei Zhan

Reconstructing dynamic 3D scenes from monocular videos remains a fundamental challenge in 3D vision. While 3D Gaussian Splatting (3DGS) achieves real-time rendering in static settings, extending it to dynamic scenes is challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Jianing Chen , Zehao Li , Yujun Cai , Hao Jiang , Chengxuan Qian , Juyuan Kang , Shuqin Gao , Honglong Zhao , Tianlu Mao , Yucheng Zhang

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

3D Gaussian Splatting (3DGS) has revolutionized 3D scene representation with superior efficiency and quality. While recent adaptations for computed tomography (CT) show promise, they struggle with severe artifacts under highly sparse-view…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Yuxiang Zhong , Jun Wei , Chaoqi Chen , Senyou An , Hui Huang

Dynamic scene reconstruction poses a persistent challenge in 3D vision. Deformable 3D Gaussian Splatting has emerged as an effective method for this task, offering real-time rendering and high visual fidelity. This approach decomposes a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Bing He , Yunuo Chen , Guo Lu , Qi Wang , Qunshan Gu , Rong Xie , Li Song , Wenjun Zhang

Gaussian splatting has emerged as a powerful tool for high-fidelity reconstruction of dynamic scenes. However, existing methods primarily rely on implicit motion representations, such as encoding motions into neural networks or per-Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Xinyu Zhang , Haonan Chang , Yuhan Liu , Abdeslam Boularias

Modeling complex rigid motion across large spatiotemporal spans remains an unresolved challenge in dynamic reconstruction. Existing paradigms are mainly confined to short-term, small-scale deformation and offer limited consideration for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Yijun Xu , Jingrui Zhang , Yuhan Chen , Dingwen Wang , Lei Yu , Chu He

Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional time-variant MLP to model scene deformations, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Diwen Wan , Ruijie Lu , Gang Zeng

In the field of 3D dynamic scene reconstruction, how to balance model convergence rate and rendering quality has long been a critical challenge that urgently needs to be addressed, particularly in high-precision modeling of scenes with…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Nengbo Lu , Minghua Pan , Shaohua Sun , Yizhou Liang

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