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Maps play an important role in autonomous driving systems. The recently proposed 3D Gaussian Splatting (3D-GS) produces rendering-quality explicit scene reconstruction results, demonstrating the potential for map construction in autonomous…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Luqi Cheng , Zhangshuo Qi , Zijie Zhou , Chao Lu , Guangming Xiong

Recently, 3D Gaussian splatting-based RGB-D SLAM displays remarkable performance of high-fidelity 3D reconstruction. However, the lack of depth rendering consistency and efficient loop closure limits the quality of its geometric…

Robotics · Computer Science 2025-06-03 Xingguang Zhong , Yue Pan , Liren Jin , Marija Popović , Jens Behley , Cyrill Stachniss

Traditional volumetric fusion algorithms preserve the spatial structure of 3D scenes, which is beneficial for many tasks in computer vision and robotics. However, they often lack realism in terms of visualization. Emerging 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Jiaxin Wei , Stefan Leutenegger

This paper presents a novel system designed for 3D mapping and visual relocalization using 3D Gaussian Splatting. Our proposed method uses LiDAR and camera data to create accurate and visually plausible representations of the environment.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Peng Jiang , Gaurav Pandey , Srikanth Saripalli

While 3D Gaussian Splatting (3DGS) enabled photorealistic mapping, its integration into SLAM has largely followed traditional camera-centric pipelines. As a result, they inherit well-known weaknesses such as high computational load, failure…

Robotics · Computer Science 2026-03-10 Jaeseok Park , Chanoh Park , Minsu Kim , Minkyoung Kim , Soohwan Kim

While generalizable 3D Gaussian splatting enables efficient, high-quality rendering of unseen scenes, it heavily depends on precise camera poses for accurate geometry. In real-world scenarios, obtaining accurate poses is challenging,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Youngju Na , Taeyeon Kim , Jumin Lee , Kyu Beom Han , Woo Jae Kim , Sung-eui Yoon

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

This paper presents GS-RoadPatching, an inpainting method for driving scene completion by referring to completely reconstructed regions, which are represented by 3D Gaussian Splatting (3DGS). Unlike existing 3DGS inpainting methods that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Guo Chen , Jiarun Liu , Sicong Du , Chenming Wu , Deqi Li , Shi-Sheng Huang , Guofeng Zhang , Sheng Yang

3D Gaussian Splatting (3DGS) achieves high-fidelity rendering with fast real-time performance, but existing methods rely on offline training after full Structure-from-Motion (SfM) processing. In contrast, this work introduces Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Yiwei Xu , Yifei Yu , Wentian Gan , Tengfei Wang , Zongqian Zhan , Hao Cheng , Xin Wang

In this paper, we introduce GS-LIVM, a real-time photo-realistic LiDAR-Inertial-Visual mapping framework with Gaussian Splatting tailored for outdoor scenes. Compared to existing methods based on Neural Radiance Fields (NeRF) and 3D…

Robotics · Computer Science 2024-10-23 Yusen Xie , Zhenmin Huang , Jin Wu , Jun Ma

Recent advancements in 3D Gaussian Splatting (3D-GS) have revolutionized novel view synthesis, facilitating real-time, high-quality image rendering. However, in scenarios involving reflective surfaces, particularly mirrors, 3D-GS often…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Zihan Wang , Shuzhe Wang , Matias Turkulainen , Junyuan Fang , Juho Kannala

Robotics applications often rely on scene reconstructions to enable downstream tasks. In this work, we tackle the challenge of actively building an accurate map of an unknown scene using an RGB-D camera on a mobile platform. We propose a…

Robotics · Computer Science 2025-04-09 Liren Jin , Xingguang Zhong , Yue Pan , Jens Behley , Cyrill Stachniss , Marija Popović

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

Rendering large-scale 3D Gaussian Splatting (3DGS) model faces significant challenges in achieving real-time, high-fidelity performance on consumer-grade devices. Fully realizing the potential of 3DGS in applications such as virtual reality…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Miao Tao , Yuanzhen Zhou , Haoran Xu , Zeyu He , Zhenyu Yang , Yuchang Zhang , Zhongling Su , Linning Xu , Zhenxiang Ma , Rong Fu , Hengjie Li , Xingcheng Zhang , Jidong Zhai

Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated remarkable capabilities in real-time and photorealistic novel view synthesis. However, traditional 3DGS representations often struggle with large-scale scene management and…

Graphics · Computer Science 2025-08-08 Zijian Wang , Beizhen Zhao , Hao Wang

3D Gaussian Splatting (3D-GS) has recently emerged as a powerful technique for real-time, photorealistic rendering by optimizing anisotropic Gaussian primitives from view-dependent images. While 3D-GS has been extended to scientific…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-16 Mengjiao Han , Andres Sewell , Joseph Insley , Janet Knowles , Victor A. Mateevitsi , Michael E. Papka , Steve Petruzza , Silvio Rizzi

We propose GGS, a Generalizable Gaussian Splatting method for Autonomous Driving which can achieve realistic rendering under large viewpoint changes. Previous generalizable 3D gaussian splatting methods are limited to rendering novel views…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Huasong Han , Kaixuan Zhou , Xiaoxiao Long , Yusen Wang , Chunxia Xiao

Recently, Gaussian Splatting, a method that represents a 3D scene as a collection of Gaussian distributions, has gained significant attention in addressing the task of novel view synthesis. In this paper, we highlight a fundamental…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Haoxuan Qu , Zhuoling Li , Hossein Rahmani , Yujun Cai , Jun Liu

3D Gaussian Splatting (3DGS) enables real-time novel view synthesis with high visual quality. However, existing methods struggle with semi-transparent specular surfaces that exhibit both complex reflections and clear transmission, often…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Ji Shi , Xianghua Ying , Bowei Xing , Ruohao Guo , Wenzhen Yue

Differentiable 3D-Gaussian splatting (GS) is emerging as a prominent technique in computer vision and graphics for reconstructing 3D scenes. GS represents a scene as a set of 3D Gaussians with varying opacities and employs a computationally…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Ziyuan Qu , Omkar Vengurlekar , Mohamad Qadri , Kevin Zhang , Michael Kaess , Christopher Metzler , Suren Jayasuriya , Adithya Pediredla
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