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While neural rendering has demonstrated impressive capabilities in 3D scene reconstruction and novel view synthesis, it heavily relies on high-quality sharp images and accurate camera poses. Numerous approaches have been proposed to train…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Lingzhe Zhao , Peng Wang , Peidong Liu

One of the key advantages of 3D rendering is its ability to simulate intricate scenes accurately. One of the most widely used methods for this purpose is Gaussian Splatting, a novel approach that is known for its rapid training and…

Graphics · Computer Science 2024-05-31 Artur Kasymov , Bartosz Czekaj , Marcin Mazur , Jacek Tabor , Przemysław Spurek

3D Gaussian Splatting (3DGS) has recently emerged as a fast, high-quality method for novel view synthesis (NVS). However, its use of low-degree spherical harmonics limits its ability to capture spatially varying color and view-dependent…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hoang Chuong Nguyen , Wei Mao , Jose M. Alvarez , Miaomiao Liu

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

Recent advancements in 3D Gaussian Splatting (3DGS) have substantially improved novel view synthesis, enabling high-quality reconstruction and real-time rendering. However, blurring artifacts, such as floating primitives and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Haodong Chen , Runnan Chen , Qiang Qu , Zhaoqing Wang , Tongliang Liu , Xiaoming Chen , Yuk Ying Chung

While 3D Gaussian Splatting (3D-GS) achieves photorealistic novel view synthesis, its performance degrades with motion blur. In scenarios with rapid motion or low-light conditions, existing RGB-based deblurring methods struggle to model…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Yufei Deng , Yuanjian Wang , Rong Xiao , Chenwei Tang , Jizhe Zhou , Jiahao Fan , Deng Xiong , Jiancheng Lv , Huajin Tang

Although significant progress has been made in reconstructing sharp 3D scenes from motion-blurred images, a transition to real-world applications remains challenging. The primary obstacle stems from the severe blur which leads to…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Jeongtaek Oh , Jaeyoung Chung , Dongwoo Lee , Kyoung Mu Lee

3D Gaussian Splatting (3D-GS) has demonstrated exceptional capabilities in 3D scene reconstruction and novel view synthesis. However, its training heavily depends on high-quality, sharp images and accurate camera poses. Fulfilling these…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Wangbo Yu , Chaoran Feng , Jiye Tang , Jiashu Yang , Zhenyu Tang , Xu Jia , Yuchao Yang , Li Yuan , Yonghong Tian

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 introduce GeMS, a framework for 3D Gaussian Splatting (3DGS) designed to handle severely motion-blurred images. State-of-the-art deblurring methods for extreme blur, such as ExBluRF, as well as Gaussian Splatting-based approaches like…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Gopi Raju Matta , Trisha Reddypalli , Vemunuri Divya Madhuri , Kaushik Mitra

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

Recent studies in Radiance Fields have paved the robust way for novel view synthesis with their photorealistic rendering quality. Nevertheless, they usually employ neural networks and volumetric rendering, which are costly to train and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Byeonghyeon Lee , Howoong Lee , Xiangyu Sun , Usman Ali , Eunbyung Park

Accurate 3D reconstruction of dynamic surgical scenes from endoscopic video is essential for robotic-assisted surgery. While recent 3D Gaussian Splatting methods have shown promise in achieving high-quality reconstructions with fast…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jialei Chen , Xin Zhang , Mobarakol Islam , Francisco Vasconcelos , Danail Stoyanov , Daniel S. Elson , Baoru Huang

3D Gaussian Splatting (3DGS) has emerged as a transformative method in the field of real-time novel synthesis. Based on 3DGS, recent advancements cope with large-scale scenes via spatial-based partition strategy to reduce video memory and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-06 Tengfei Wang , Xin Wang , Yongmao Hou , Yiwei Xu , Wendi Zhang , Zongqian Zhan

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Danpeng Chen , Hai Li , Weicai Ye , Yifan Wang , Weijian Xie , Shangjin Zhai , Nan Wang , Haomin Liu , Hujun Bao , Guofeng Zhang

Due to the real-time rendering performance, 3D Gaussian Splatting (3DGS) has emerged as the leading method for radiance field reconstruction. However, its reliance on spherical harmonics for color encoding inherently limits its ability to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Yixin Yang , Bojian Wu , Yang Zhou , Hui Huang

Implicit neural representation methods have shown impressive advancements in learning 3D scenes from unstructured in-the-wild photo collections but are still limited by the large computational cost of volumetric rendering. More recently, 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Hiba Dahmani , Moussab Bennehar , Nathan Piasco , Luis Roldao , Dzmitry Tsishkou

3D Gaussian Splatting has exhibited remarkable capabilities in 3D scene reconstruction. However, reconstructing high-quality 3D scenes from motion-blurred images caused by camera motion poses a significant challenge.The performance of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 An Zhao , Piaopiao Yu , Zhe Zhu , Mingqiang Wei

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

The reconstruction of 3D objects from calibrated photographs represents a fundamental yet intricate challenge in the domains of computer graphics and vision. Although neural reconstruction approaches based on Neural Radiance Fields (NeRF)…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Bang Du , Runfa Blark Li , Chen Du , Truong Nguyen
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