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Most 3D Gaussian Splatting (3D-GS) based methods for urban scenes initialize 3D Gaussians directly with 3D LiDAR points, which not only underutilizes LiDAR data capabilities but also overlooks the potential advantages of fusing LiDAR with…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Cheng Zhao , Su Sun , Ruoyu Wang , Yuliang Guo , Jun-Jun Wan , Zhou Huang , Xinyu Huang , Yingjie Victor Chen , Liu Ren

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

We present a framework that enables fast reconstruction and real-time rendering of urban-scale scenes while maintaining robustness against appearance variations across multi-view captures. Our approach begins with scene partitioning for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhensheng Yuan , Haozhi Huang , Zhen Xiong , Di Wang , Guanghua Yang

3D Gaussian Splatting (3DGS) achieves remarkable results in the field of surface reconstruction. However, when Gaussian normal vectors are aligned within the single-view projection plane, while the geometry appears reasonable in the current…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Bo Jia , Yanan Guo , Ying Chang , Benkui Zhang , Ying Xie , Kangning Du , Lin Cao

3D Gaussian Splatting has recently emerged as a highly promising technique for modeling of static 3D scenes. In contrast to Neural Radiance Fields, it utilizes efficient rasterization allowing for very fast rendering at high-quality.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Wieland Morgenstern , Florian Barthel , Anna Hilsmann , Peter Eisert

Localization and mapping are critical tasks for various applications such as autonomous vehicles and robotics. The challenges posed by outdoor environments present particular complexities due to their unbounded characteristics. In this…

Robotics · Computer Science 2024-04-08 Chenyang Wu , Yifan Duan , Xinran Zhang , Yu Sheng , Jianmin Ji , Yanyong Zhang

3D urban scene reconstruction and modelling is a crucial research area in remote sensing with numerous applications in academia, commerce, industry, and administration. Recent advancements in view synthesis models have facilitated…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Kyle Gao , Dening Lu , Hongjie He , Linlin Xu , Jonathan Li

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

This paper introduces LiGSM, a novel LiDAR-enhanced 3D Gaussian Splatting (3DGS) mapping framework that improves the accuracy and robustness of 3D scene mapping by integrating LiDAR data. LiGSM constructs joint loss from images and LiDAR…

Robotics · Computer Science 2025-03-10 Jian Shen , Huai Yu , Ji Wu , Wen Yang , Gui-Song Xia

Accurate geometric surface reconstruction, providing essential environmental information for navigation and manipulation tasks, is critical for enabling robotic self-exploration and interaction. Recently, 3D Gaussian Splatting (3DGS) has…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Tengfei Wang , Xin Wang , Yongmao Hou , Zhaoning Zhang , Yiwei Xu , Zongqian Zhan

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

This paper presents a 3D lidar SLAM system based on improved regionalized Gaussian process (GP) map reconstruction to provide both low-drift state estimation and mapping in real-time for robotics applications. We utilize spatial GP…

Robotics · Computer Science 2023-03-10 Jianyuan Ruan , Bo Li , Yinqiang Wang , Zhou Fang

3D Gaussian Splatting (3DGS) effectively synthesizes novel views through its flexible representation, yet fails to accurately reconstruct scene geometry. While modern variants like PGSR introduce additional losses to ensure proper depth and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zhentao Huang , Di Wu , Zhenbang He , Minglun Gong

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

Differentiable 3D Gaussian splatting has emerged as an efficient and flexible rendering technique for representing complex scenes from a collection of 2D views and enabling high-quality real-time novel-view synthesis. However, its reliance…

Graphics · Computer Science 2025-01-16 Meenakshi Krishnan , Liam Fowl , Ramani Duraiswami

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

Recently, generalizable human Gaussian splatting from sparse-view inputs has been actively studied for the photorealistic human rendering. Most existing methods rely on explicit geometric constraints or predefined structural representations…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Jingi Kim , Wonjun Kim

3D Gaussian Splatting (3DGS) techniques have achieved satisfactory 3D scene representation. Despite their impressive performance, they confront challenges due to the limitation of structure-from-motion (SfM) methods on acquiring accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Ao Gao , Luosong Guo , Tao Chen , Zhao Wang , Ying Tai , Jian Yang , Zhenyu Zhang

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

High-fidelity 3D reconstruction of common indoor scenes is crucial for VR and AR applications. 3D Gaussian splatting, a novel differentiable rendering technique, has achieved state-of-the-art novel view synthesis results with high rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Matias Turkulainen , Xuqian Ren , Iaroslav Melekhov , Otto Seiskari , Esa Rahtu , Juho Kannala