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Feed-forward 3D Gaussian Splatting (FF-3DGS) emerges as a fast and robust solution for sparse-view 3D reconstruction and novel view synthesis (NVS). However, existing FF-3DGS methods are built on incorrect screen-space dilation filters,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Taewoo Suh , Sungpyo Kim , Jongmin Park , Munchurl Kim

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

Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimization. However, existing feedforward approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anran Wu , Long Peng , Xin Di , Xueyuan Dai , Chen Wu , Yang Wang , Xueyang Fu , Yang Cao , Zheng-Jun Zha

We present 3DGS-LM, a new method that accelerates the reconstruction of 3D Gaussian Splatting (3DGS) by replacing its ADAM optimizer with a tailored Levenberg-Marquardt (LM). Existing methods reduce the optimization time by decreasing the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Lukas Höllein , Aljaž Božič , Michael Zollhöfer , Matthias Nießner

3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limited scenes. In this paper, we make the first attempt to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Junyi Chen , Weicai Ye , Yifan Wang , Danpeng Chen , Di Huang , Wanli Ouyang , Guofeng Zhang , Yu Qiao , Tong He

3D gaussian splatting has advanced simultaneous localization and mapping (SLAM) technology by enabling real-time positioning and the construction of high-fidelity maps. However, the uncertainty in gaussian position and initialization…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Yansong Xu , Junlin Li , Wei Zhang , Siyu Chen , Shengyong Zhang , Yuquan Leng , Weijia Zhou

Simultaneous Localization and Mapping (SLAM) with dense representation plays a key role in robotics, Virtual Reality (VR), and Augmented Reality (AR) applications. Recent advancements in dense representation SLAM have highlighted the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Seongbo Ha , Jiung Yeon , Hyeonwoo Yu

The underwater 3D scene reconstruction is a challenging, yet interesting problem with applications ranging from naval robots to VR experiences. The problem was successfully tackled by fully volumetric NeRF-based methods which can model both…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Huapeng Li , Wenxuan Song , Tianao Xu , Alexandre Elsig , Jonas Kulhanek

3D Gaussian Splatting (3DGS) has emerged as a mainstream solution for novel view synthesis and 3D reconstruction. By explicitly encoding a 3D scene using a collection of Gaussian kernels, 3DGS achieves high-quality rendering with superior…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Lei Lan , Tianjia Shao , Zixuan Lu , Yu Zhang , Chenfanfu Jiang , Yin Yang

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

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

Collaborative photorealistic 3D reconstruction from multiple agents enables rapid large-scale scene capture for virtual production and cooperative multi-robot exploration. While recent 3D Gaussian Splatting (3DGS) SLAM algorithms can…

Robotics · Computer Science 2026-05-12 Zhihao Cao , Qi Shao , Shuhao Zhai , Jing Zhang , Anh Nguyen , Baoru Huang

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

This study addresses the challenge of accurately segmenting 3D Gaussian Splatting from 2D masks. Conventional methods often rely on iterative gradient descent to assign each Gaussian a unique label, leading to lengthy optimization and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Qiuhong Shen , Xingyi Yang , Xinchao Wang

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

Recently, 3D Gaussian Splatting (3DGS) has demonstrated excellent ability in small-scale 3D surface reconstruction. However, extending 3DGS to large-scale scenes remains a significant challenge. To address this gap, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 YuanZheng Wu , Jin Liu , Shunping Ji

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

State-of-the-art methods for large-scale 3D reconstruction from RGB-D sensors usually reduce drift in camera tracking by globally optimizing the estimated camera poses in real-time without simultaneously updating the reconstructed surface…

Computer Vision and Pattern Recognition · Computer Science 2017-09-13 Robert Maier , Raphael Schaller , Daniel Cremers

Recently, 3D Gaussian Splatting (3DGS) has reshaped the field of photorealistic 3D reconstruction, achieving impressive rendering quality and speed. However, when applied to large-scale street scenes, existing methods suffer from rapidly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Guangting Zheng , Jiajun Deng , Xiaomeng Chu , Yu Yuan , Houqiang Li , Yanyong Zhang

Recent significant advances in 3D scene representation have been driven by 3D Gaussian Splatting (3DGS), which has enabled real-time rendering with photorealistic quality. 3DGS often requires a large number of primitives to achieve high…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Haoran Wang , Guoxi Huang , Fan Zhang , David Bull , Nantheera Anantrasirichai