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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

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

3D Gaussian Splatting offers expressive scene reconstruction, modeling a broad range of visual, geometric, and semantic information. However, efficient real-time map reconstruction with data streamed from multiple robots and devices remains…

Robotics · Computer Science 2025-06-04 Javier Yu , Timothy Chen , Mac Schwager

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

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

3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of Computer Graphics, offering explicit scene representation and novel view synthesis without the reliance on neural networks, such as Neural Radiance…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Ben Fei , Jingyi Xu , Rui Zhang , Qingyuan Zhou , Weidong Yang , Ying He

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin

We introduce GaussianZoom, a generative zoom-in 3D reconstruction system with an iterative progressive framework that combines geometry-consistent scene modeling and multi-scale semantic reasoning to enable high-fidelity extreme zoom-in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jiale Shi , Jiarui Hu , Zesong Yang , Kaixuan Luan , Hujun Bao , Zhaopeng Cui

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

3D Gaussian Splatting has garnered extensive attention and application in real-time neural rendering. Concurrently, concerns have been raised about the limitations of this technology in aspects such as point cloud storage, performance, and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Letian Huang , Jiayang Bai , Jie Guo , Yuanqi Li , Yanwen Guo

3D Gaussian Splatting (3DGS) enables efficient training and fast novel view synthesis in static environments. To address challenges posed by transient objects, distractor-free 3DGS methods have emerged and shown promising results when dense…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yi Gu , Zhaorui Wang , Jiahang Cao , Jiaxu Wang , Mingle Zhao , Dongjun Ye , Renjing Xu

In this paper, we present a method for localizing a query image with respect to a precomputed 3D Gaussian Splatting (3DGS) scene representation. First, the method uses 3DGS to render a synthetic RGBD image at some initial pose estimate.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Jongwon Lee , Timothy Bretl

We propose DrivingForward, a feed-forward Gaussian Splatting model that reconstructs driving scenes from flexible surround-view input. Driving scene images from vehicle-mounted cameras are typically sparse, with limited overlap, and the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Qijian Tian , Xin Tan , Yuan Xie , Lizhuang Ma

Recent feed-forward Gaussian reconstruction models adopt a pixel-aligned formulation that maps each 2D pixel to a 3D Gaussian, entangling Gaussian representations tightly with the input images. In this paper, we propose AnchorSplat, a novel…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Xiaoxue Zhang , Xiaoxu Zheng , Yixuan Yin , Tiao Zhao , Kaihua Tang , Michael Bi Mi , Zhan Xu , Dave Zhenyu Chen

We observe that Gaussians exhibit distinct roles and characteristics analogous to traditional artistic techniques -- like how artists first sketch outlines before filling in broader areas with color, some Gaussians capture high-frequency…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yuang Shi , Géraldine Morin , Simone Gasparini , Wei Tsang Ooi

Gaussian splatting typically requires dense observations of the scene and can fail to reconstruct occluded and unobserved areas. We propose a latent diffusion model to reconstruct a complete 3D scene with Gaussian splats, including the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Ziwei Liao , Mohamed Sayed , Steven L. Waslander , Sara Vicente , Daniyar Turmukhambetov , Michael Firman

Recently, the integration of the efficient feed-forward scheme into 3D Gaussian Splatting (3DGS) has been actively explored. However, most existing methods focus on sparse view reconstruction of small regions and cannot produce eligible…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

3D Gaussian Splatting (3DGS) has shown promising results for 3D scene modeling using mixtures of Gaussians, yet its existing simultaneous localization and mapping (SLAM) variants typically rely on direct, deterministic pose optimization…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Yuhan Zhu , Yanyu Zhang , Jie Xu , Wei Ren

Ray-tracing-based 3D Gaussian splatting (3DGS) methods overcome the limitations of rasterization -- rigid pinhole camera assumptions, inaccurate shadows, and lack of native reflection or refraction -- but remain slower due to the cost of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Peiyu Xu , Xin Sun , Krishna Mullia , Raymond Fei , Iliyan Georgiev , Shuang Zhao

Accurate 3D reconstruction of vehicles is vital for applications such as vehicle inspection, predictive maintenance, and urban planning. Existing methods like Neural Radiance Fields and Gaussian Splatting have shown impressive results but…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Davide Di Nucci , Matteo Tomei , Guido Borghi , Luca Ciuffreda , Roberto Vezzani , Rita Cucchiara