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Related papers: 4C4D: 4 Camera 4D Gaussian Splatting

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High-fidelity reconstruction of dynamic scenes is an important yet challenging problem. While recent 4D Gaussian Splatting (4DGS) has demonstrated the ability to model temporal dynamics, it couples Gaussian motion and geometric attributes…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yi Zhang , Yulei Kang , Jiangxin Sun , Beihao Xia , Jisheng Dang , Jian-Fang Hu

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Traditional methods relying on dense point clouds and triangular meshes struggle with moving…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peizhen Zheng , Dongjing Jiang , Qingchong Jiao , Redouane EL Bouchtaoui , Flynnwell Jianfei Zhang

The advent of 3D Gaussian Splatting (3D-GS) techniques and their dynamic scene modeling variants, 4D-GS, offers promising prospects for real-time rendering of dynamic surgical scenarios. However, the prerequisite for modeling dynamic scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Hengyu Liu , Yifan Liu , Chenxin Li , Wuyang Li , Yixuan Yuan

Capturing and reconstructing high-speed dynamic 3D scenes has numerous applications in computer graphics, vision, and interdisciplinary fields such as robotics, aerodynamics, and evolutionary biology. However, achieving this using a single…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Zihao Zou , Ziyuan Qu , Xi Peng , Vivek Boominathan , Adithya Pediredla , Praneeth Chakravarthula

High-fidelity reconstruction of surgical scene is a fundamentally crucial task to support many applications, such as intra-operative navigation and surgical education. However, most existing methods assume the ideal surgical scenarios -…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Qian Li , Shuojue Yang , Daiyun Shen , Jimmy Bok Yan So , Jing Qin , Yueming Jin

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

4D Gaussian Splatting has emerged as a new paradigm for dynamic scene representation, enabling real-time rendering of scenes with complex motions. However, it faces a major challenge of storage overhead, as millions of Gaussians are…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Minseo Lee , Byeonghyeon Lee , Lucas Yunkyu Lee , Eunsoo Lee , Sangmin Kim , Seunghyeon Song , Joo Chan Lee , Jong Hwan Ko , Jaesik Park , Eunbyung Park

Reconstructing and understanding 3D scenes from unposed sparse views in a feed-forward manner remains as a challenging task in 3D computer vision. Recent approaches use per-pixel 3D Gaussian Splatting for reconstruction, followed by a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Honggyu An , Jaewoo Jung , Mungyeom Kim , Chaehyun Kim , Minkyeong Jeon , Jisang Han , Kazumi Fukuda , Takuya Narihira , Hyuna Ko , Junsu Kim , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

Understanding dynamic scenes from casual videos is critical for scalable robot learning, yet four-dimensional (4D) reconstruction under strictly monocular settings remains highly ill-posed. To address this challenge, our key insight is that…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Can Li , Jie Gu , Jingmin Chen , Fangzhou Qiu , Lei Sun

Reconstructing clean, distractor-free 3D scenes from real-world captures remains a significant challenge, particularly in highly dynamic and cluttered settings such as egocentric videos. To tackle this problem, we introduce DeGauss, a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Rui Wang , Quentin Lohmeyer , Mirko Meboldt , Siyu Tang

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rendering, achieving very fast rendering speed and promising…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aquatic environments. This paper presents an enhanced Gaussian Splatting-based framework that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

With the popularity of monocular videos generated by video sharing and live broadcasting applications, reconstructing and editing dynamic scenes in stationary monocular cameras has become a special but anticipated technology. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Weixing Xie , Xiao Dong , Yong Yang , Qiqin Lin , Jingze Chen , Junfeng Yao , Xiaohu Guo

Maintaining consistent 3D scene representations over time is a significant challenge in computer vision. Updating 3D scenes from sparse-view observations is crucial for various real-world applications, including urban planning, disaster…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Zeyuan An , Yanghang Xiao , Zhiying Leng , Frederick W. B. Li , Xiaohui Liang

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

The synthesis of spatiotemporally coherent 4D content presents fundamental challenges in computer vision, requiring simultaneous modeling of high-fidelity spatial representations and physically plausible temporal dynamics. Current…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Xiaoyan Liu , Kangrui Li , Yuehao Song , Jiaxin Liu

Deformable Gaussian Splatting (GS) accomplishes photorealistic dynamic 3-D reconstruction from dense multi-view video (MVV) by learning to deform a canonical GS representation. However, in filmmaking, tight budgets can result in sparse…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Adrian Azzarelli , Nantheera Anantrasirichai , David R Bull

Surgical simulation is essential for medical training, enabling practitioners to develop crucial skills in a risk-free environment while improving patient safety and surgical outcomes. However, conventional methods for building simulation…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Zhenya Yang

Modeling dynamic scenes through 4D Gaussians offers high visual fidelity and fast rendering speeds, but comes with significant storage overhead. Recent approaches mitigate this cost by aggressively reducing the number of Gaussians. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Woong Oh Cho , In Cho , Seoha Kim , Jeongmin Bae , Youngjung Uh , Seon Joo Kim