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Related papers: ExploreGS: Explorable 3D Scene Reconstruction with…

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3D Gaussian Splatting (3DGS) has revolutionized neural rendering with its efficiency and quality, but like many novel view synthesis methods, it heavily depends on accurate camera poses from Structure-from-Motion (SfM) systems. Although…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhisheng Huang , Peng Wang , Jingdong Zhang , Yuan Liu , Xin Li , Wenping Wang

Novel View Synthesis plays a crucial role by generating new 2D renderings from multi-view images of 3D scenes. However, capturing high-speed scenes with conventional cameras often leads to motion blur, hindering the effectiveness of 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Jiyuan Zhang , Kang Chen , Shiyan Chen , Yajing Zheng , Tiejun Huang , Zhaofei Yu

Implicit neural representation and explicit 3D Gaussian Splatting (3D-GS) for novel view synthesis have achieved remarkable progress with frame-based camera (e.g. RGB and RGB-D cameras) recently. Compared to frame-based camera, a novel type…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Jian Huang , Chengrui Dong , Xuanhua Chen , Peidong Liu

Despite recent successes in novel view synthesis using 3D Gaussian Splatting (3DGS), modeling scenes with sparse inputs remains a challenge. In this work, we address two critical yet overlooked issues in real-world sparse-input modeling:…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Yingji Zhong , Zhihao Li , Dave Zhenyu Chen , Lanqing Hong , Dan Xu

In underwater images, most useful features are occluded by water. The extent of the occlusion depends on imaging geometry and can vary even across a sequence of burst images. As a result, 3D reconstruction methods robust on in-air scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Nir Mualem , Roy Amoyal , Oren Freifeld , Derya Akkaynak

3D Gaussian Splatting (3DGS) has significantly advanced 3D scene reconstruction and novel view synthesis. However, like Neural Radiance Fields (NeRF), 3DGS struggles with accurately modeling physical reflections, particularly in mirrors,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Jiarui Meng , Haijie Li , Yanmin Wu , Qiankun Gao , Shuzhou Yang , Jian Zhang , Siwei Ma

We introduce SeaSplat, a method to enable real-time rendering of underwater scenes leveraging recent advances in 3D radiance fields. Underwater scenes are challenging visual environments, as rendering through a medium such as water…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Daniel Yang , John J. Leonard , Yogesh Girdhar

Real-time 3D reconstruction of surgical scenes plays a vital role in computer-assisted surgery, holding a promise to enhance surgeons' visibility. Recent advancements in 3D Gaussian Splatting (3DGS) have shown great potential for real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Jiaxin Guo , Jiangliu Wang , Di Kang , Wenzhen Dong , Wenting Wang , Yun-hui Liu

Since its introduction, 3D Gaussian Splatting (3DGS) has become an important reference method for learning 3D representations of a captured scene, allowing real-time novel-view synthesis with high visual quality and fast training times.…

Graphics · Computer Science 2025-02-27 Adam Celarek , George Kopanas , George Drettakis , Michael Wimmer , Bernhard Kerbl

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promising results separately handling dynamic scenes (4DGS) and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Although subsequent efforts rapidly extend static 3D Gaussian to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Ruijie Zhu , Yanzhe Liang , Hanzhi Chang , Jiacheng Deng , Jiahao Lu , Wenfei Yang , Tianzhu Zhang , Yongdong Zhang

Novel view synthesis has seen major advances in recent years, with 3D Gaussian splatting offering an excellent level of visual quality, fast training and real-time rendering. However, the resources needed for training and rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Bernhard Kerbl , Andréas Meuleman , Georgios Kopanas , Michael Wimmer , Alexandre Lanvin , George Drettakis

3D Gaussian splatting (GS) has emerged as a transformative technique in radiance fields. Unlike mainstream implicit neural models, 3D GS uses millions of learnable 3D Gaussians for an explicit scene representation. Paired with a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Guikun Chen , Wenguan Wang

Reconstructing static 3D scene from monocular video with dynamic objects is important for numerous applications such as virtual reality and autonomous driving. Current approaches typically rely on background for static scene reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Yedong Shen , Shiqi Zhang , Sha Zhang , Yifan Duan , Xinran Zhang , Wenhao Yu , Lu Zhang , Jiajun Deng , Yanyong Zhang

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 (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

Recently, Gaussian Splatting methods have emerged as a desirable substitute for prior Radiance Field methods for novel-view synthesis of scenes captured with multi-view images or videos. In this work, we propose a novel extension to 4D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Karly Hou , Wanhua Li , Hanspeter Pfister

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

Recent advancements in high-fidelity dynamic scene reconstruction have leveraged dynamic 3D Gaussians and 4D Gaussian Splatting for realistic scene representation. However, to make these methods viable for real-time applications such as…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Saqib Javed , Ahmad Jarrar Khan , Corentin Dumery , Chen Zhao , Mathieu Salzmann

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