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Related papers: LiDAR-enhanced 3D Gaussian Splatting Mapping

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Structure from Motion (SfM) often fails to estimate accurate poses in environments that lack suitable visual features. In such cases, the quality of the final 3D mesh, which is contingent on the accuracy of those estimates, is reduced. One…

Computer Vision and Pattern Recognition · Computer Science 2021-04-08 Victor Amblard , Timothy P. Osedach , Arnaud Croux , Andrew Speck , John J. Leonard

We propose a novel cross-spectral rendering framework based on 3D Gaussian Splatting (3DGS) that generates realistic and semantically meaningful splats from registered multi-view spectrum and segmentation maps. This extension enhances the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Saptarshi Neil Sinha , Holger Graf , Michael Weinmann

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

3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage requirements and inherently unstructured representation pose challenges for deployment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Yuqin Lu , Yang Zhou , Yihua Dai , Guiqing Li , Shengfeng He

We present F3DGS, a federated 3D Gaussian Splatting framework for decentralized multi-agent 3D reconstruction. Existing 3DGS pipelines assume centralized access to all observations, which limits their applicability in distributed robotic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Morui Zhu , Mohammad Dehghani Tezerjani , Mátyás Szántó , Márton Vaitkus , Song Fu , Qing Yang

Recent trends in SLAM and visual navigation have embraced 3D Gaussians as the preferred scene representation, highlighting the importance of estimating camera poses from a single image using a pre-built Gaussian model. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hao Wang , Linqing Zhao , Xiuwei Xu , Jiwen Lu , Haibin Yan

We present a dense simultaneous localization and mapping (SLAM) method that uses 3D Gaussians as a scene representation. Our approach enables interactive-time reconstruction and photo-realistic rendering from real-world single-camera RGBD…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Vladimir Yugay , Yue Li , Theo Gevers , Martin R. Oswald

Recent advances in Dense Simultaneous Localization and Mapping (SLAM) have demonstrated remarkable performance in static environments. However, dense SLAM in dynamic environments remains challenging. Most methods directly remove dynamic…

Robotics · Computer Science 2025-12-11 Siting Zhu , Yuxiang Huang , Wenhua Wu , Chaokang Jiang , Yongbo Chen , I-Ming Chen , Hesheng Wang

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time LiDAR and camera synthesis in autonomous driving simulation. However, simulating LiDAR with 3DGS remains challenging for extrapolated views beyond the training…

Robotics · Computer Science 2026-03-17 Yiming Huang , Xin Kang , Sipeng Zhang , Hongliang Ren , Weihua Zhang , Junjie Lai

Navigation and mapping on the lunar surface require robust perception under challenging conditions, including poorly textured environments, high-contrast lighting, and limited computational resources. This paper presents a real-time mapping…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Guillem Casadesus Vila , Adam Dai , Grace Gao

The advancement of real-time 3D scene reconstruction and novel view synthesis has been significantly propelled by 3D Gaussian Splatting (3DGS). However, effectively training large-scale 3DGS and rendering it in real-time across various…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yang Liu , He Guan , Chuanchen Luo , Lue Fan , Naiyan Wang , Junran Peng , Zhaoxiang Zhang

We propose a dense RGBD SLAM system based on 3D Gaussian Splatting that provides metrically accurate pose tracking and visually realistic reconstruction. To this end, we first propose a Gaussian densification strategy based on the rendering…

Robotics · Computer Science 2024-10-03 Shuo Sun , Malcolm Mielle , Achim J. Lilienthal , Martin Magnusson

We present Rad-GS, a 4D radar-camera SLAM system designed for kilometer-scale outdoor environments, utilizing 3D Gaussian as a differentiable spatial representation. Rad-GS combines the advantages of raw radar point cloud with Doppler…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Renxiang Xiao , Wei Liu , Yuanfan Zhang , Yushuai Chen , Jinming Chen , Zilu Wang , Liang Hu

3D scene reconstruction and rendering are core tasks in computer vision, with applications spanning industrial monitoring, robotics, and autonomous driving. Recent advances in 3D Gaussian Splatting (GS) and its variants have achieved…

Computer Vision and Pattern Recognition · Computer Science 2026-02-20 Chi-Shiang Gau , Konstantinos D. Polyzos , Athanasios Bacharis , Saketh Madhuvarasu , Tara Javidi

This paper presents DENSER, an efficient and effective approach leveraging 3D Gaussian splatting (3DGS) for the reconstruction of dynamic urban environments. While several methods for photorealistic scene representations, both implicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Mahmud A. Mohamad , Gamal Elghazaly , Arthur Hubert , Raphael Frank

This paper introduces MipSLAM, a frequency-aware 3D Gaussian Splatting (3DGS) SLAM framework capable of high-fidelity anti-aliased novel view synthesis and robust pose estimation under varying camera configurations. Existing 3DGS-based SLAM…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yingzhao Li , Yan Li , Shixiong Tian , Yanjie Liu , Lijun Zhao , Gim Hee Lee

This study addresses the challenge of online 3D model generation for neural rendering using an RGB image stream. Previous research has tackled this issue by incorporating Neural Radiance Fields (NeRF) or 3D Gaussian Splatting (3DGS) as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Byeonggwon Lee , Junkyu Park , Khang Truong Giang , Sungho Jo , Soohwan Song

Dynamic scene reconstruction has garnered significant attention in recent years due to its capabilities in high-quality and real-time rendering. Among various methodologies, constructing a 4D spatial-temporal representation, such as 4D-GS,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Weiwei Cai , Weicai Ye , Peng Ye , Tong He , Tao Chen

LiDARs provide accurate geometric measurements, making them valuable for ego-motion estimation and reconstruction tasks. Although its success, managing an accurate and lightweight representation of the environment still poses challenges.…

Recent work has shown that 3D Gaussian-based SLAM enables high-quality reconstruction, accurate pose estimation, and real-time rendering of scenes. However, these approaches are built on a tremendous number of redundant 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Tianchen Deng , Chang Nie , Shuhong Liu , Wenhua Wu , Jianfei Yang , Shenghai Yuan , Jiuming Liu , Danwei Wang , Hesheng Wang