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The advent of 3D Gaussian Splatting has revolutionized graphics rendering by delivering high visual quality and fast rendering speeds. However, training large-scale scenes at high quality remains challenging due to the substantial memory…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Donghyun Lee , Dawoon Jeong , Jae W. Lee , Hongil Yoon

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

3D Gaussian Splatting (3DGS) has gained significant attention for their 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 2024-12-10 Jungho Lee , Donghyeong Kim , Dogyoon Lee , Suhwan Cho , Minhyeok Lee , Sangyoun Lee

3D Gaussian Splatting (3DGS) has made significant strides in scene representation and neural rendering, with intense efforts focused on adapting it for dynamic scenes. Despite delivering remarkable rendering quality and speed, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sangwoon Kwak , Joonsoo Kim , Jun Young Jeong , Won-Sik Cheong , Jihyong Oh , Munchurl Kim

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

Robust and realistic rendering for large-scale road scenes is essential in autonomous driving simulation. Recently, 3D Gaussian Splatting (3D-GS) has made groundbreaking progress in neural rendering, but the general fidelity of large-scale…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Saining Zhang , Baijun Ye , Xiaoxue Chen , Yuantao Chen , Zongzheng Zhang , Cheng Peng , Yongliang Shi , Hao Zhao

In recent years, 3D Gaussian Splatting (3D-GS)-based scene representation demonstrates significant potential in real-time rendering and training efficiency. However, most existing methods primarily focus on single-map reconstruction, while…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Shiyang Liu , Dianyi Yang , Yu Gao , Bohan Ren , Yi Yang , Mengyin Fu

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

Standard 3D Gaussian Splatting (3DGS) relies on known or pre-computed camera poses and a sparse point cloud, obtained from structure-from-motion (SfM) preprocessing, to initialize and grow 3D Gaussians. We propose a novel SfM-Free 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Bo Ji , Angela Yao

3D Gaussian Splatting (3DGS) has revolutionized novel view synthesis with high-quality rendering through continuous aggregations of millions of 3D Gaussian primitives. However, it suffers from a substantial memory footprint, particularly…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Yangming Zhang , Jian Xu , Chaojian Li , Kunxiong Zhu , Wei Niu , Gagan Agrawal , Yang Katie Zhao , Jian Wang , Yingyan Celine Lin , Miao Yin

Gaussian Splatting (GS) is a novel, state-of-the-art technique for rendering points in a 3D scene by approximating their contribution to image pixels through Gaussian distributions, warranting fast training and real-time rendering. The main…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Joanna Waczyńska , Piotr Borycki , Sławomir Tadeja , Jacek Tabor , Przemysław Spurek

Dynamic videos with small baseline motions are ubiquitous in daily life, especially on social media. However, these videos present a challenge to existing pose estimation frameworks due to ambiguous features, drift accumulation, and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Yuxin Yao , Yan Zhang , Zhening Huang , Joan Lasenby

We consider the problem of novel-view synthesis (NVS) for dynamic scenes. Recent neural approaches have accomplished exceptional NVS results for static 3D scenes, but extensions to 4D time-varying scenes remain non-trivial. Prior efforts…

Computer Vision and Pattern Recognition · Computer Science 2024-07-03 Yuanxing Duan , Fangyin Wei , Qiyu Dai , Yuhang He , Wenzheng Chen , Baoquan Chen

Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem. Despite recent advancements, simultaneously achieving high-resolution photorealistic results, real-time rendering, and compact storage remains a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Zhan Li , Zhang Chen , Zhong Li , Yi Xu

3D Gaussian Splatting (3DGS) has made significant strides in real-time 3D scene reconstruction, but faces memory scalability issues in high-resolution scenarios. To address this, we propose Hierarchical Gaussian Splatting (HRGS), a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Changbai Li , Haodong Zhu , Hanlin Chen , Juan Zhang , Tongfei Chen , Shuo Yang , Shuwei Shao , Wenhao Dong , Baochang Zhang

3D Gaussian Splatting (3DGS) has demonstrated impressive Novel View Synthesis (NVS) results in a real-time rendering manner. During training, it relies heavily on the average magnitude of view-space positional gradients to grow Gaussians to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Qingshan Xu , Jiequan Cui , Xuanyu Yi , Yuxuan Wang , Yuan Zhou , Yew-Soon Ong , Hanwang Zhang

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time, high-resolution novel view synthesis. By representing scenes as a mixture of Gaussian primitives, 3DGS leverages GPU rasterization pipelines for efficient…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Peihao Wang , Yuehao Wang , Dilin Wang , Sreyas Mohan , Zhiwen Fan , Lemeng Wu , Ruisi Cai , Yu-Ying Yeh , Zhangyang Wang , Qiang Liu , Rakesh Ranjan

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

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction. However, most existing GS-based surface reconstruction methods focus on 3D objects or limited scenes. Directly applying these methods to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Yuanyuan Gao , Yalun Dai , Hao Li , Weicai Ye , Junyi Chen , Danpeng Chen , Dingwen Zhang , Tong He , Guofeng Zhang , Junwei Han

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promising results separately handling dynamic scenes (4DGS) and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu
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