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We present a novel method for 6-DoF object tracking and high-quality 3D reconstruction from monocular RGBD video. Existing methods, while achieving impressive results, often struggle with complex objects, particularly those exhibiting…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Takuya Ikeda , Sergey Zakharov , Muhammad Zubair Irshad , Istvan Balazs Opra , Shun Iwase , Dian Chen , Mark Tjersland , Robert Lee , Alexandre Dilly , Rares Ambrus , Koichi Nishiwaki

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

Gaussian Splatting (GS) has gained attention as a fast and effective method for novel view synthesis. It has also been applied to 3D reconstruction using multi-view images and can achieve fast and accurate 3D reconstruction. However, GS…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Natsuki Takama , Shintaro Ito , Koichi Ito , Hwann-Tzong Chen , Takafumi Aoki

In this work, we present Fed3DGS, a scalable 3D reconstruction framework based on 3D Gaussian splatting (3DGS) with federated learning. Existing city-scale reconstruction methods typically adopt a centralized approach, which gathers all…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Teppei Suzuki

We present a Gaussian Splatting method for surface reconstruction using sparse input views. Previous methods relying on dense views struggle with extremely sparse Structure-from-Motion points for initialization. While learning-based…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Jiang Wu , Rui Li , Yu Zhu , Rong Guo , Jinqiu Sun , Yanning Zhang

Recently, 3D Gaussian Splatting has emerged as a prominent research direction owing to its ultrarapid training speed and high-fidelity rendering capabilities. However, the unstructured and irregular nature of Gaussian point clouds poses…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Xiao Ren , Yu Liu , Ning An , Jian Cheng , Xin Qiao , He Kong

Differentiable rendering with 3D Gaussian primitives has emerged as a powerful method for reconstructing high-fidelity 3D scenes from multi-view images. While it offers improvements over NeRF-based methods, this representation still…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Kaifeng Sheng , Zheng Zhou , Yingliang Peng , Qianwei Wang

While 3D Gaussian Splatting (3DGS) enables high-quality, real-time rendering for bounded scenes, its extension to large-scale urban environments gives rise to critical challenges in terms of geometric consistency, memory efficiency, and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Changbai Li , Haodong Zhu , Hanlin Chen , Xiuping Liang , Tongfei Chen , Shuwei Shao , Linlin Yang , Huobin Tan , Baochang Zhang

Recent 3D Gaussian Splatting (3DGS) representations have demonstrated remarkable performance in novel view synthesis; further, material-lighting disentanglement on 3DGS warrants relighting capabilities and its adaptability to broader…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Kai Ye , Chong Gao , Guanbin Li , Wenzheng Chen , Baoquan Chen

We present the first application of 3D Gaussian Splatting in monocular SLAM, the most fundamental but the hardest setup for Visual SLAM. Our method, which runs live at 3fps, utilises Gaussians as the only 3D representation, unifying the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Hidenobu Matsuki , Riku Murai , Paul H. J. Kelly , Andrew J. Davison

Recent advancements in 3D Gaussian Splatting (3DGS), which lead to high-quality novel view synthesis and accelerated rendering, have remarkably improved the quality of radiance field reconstruction. However, the extraction of mesh from a…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Shengchao Zhao , Yundong Li

Dynamic scene reconstruction from monocular video is essential for real-world applications. We introduce DGNS, a hybrid framework integrating \underline{D}eformable \underline{G}aussian Splatting and Dynamic \underline{N}eural…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Xuesong Li , Jinguang Tong , Jie Hong , Vivien Rolland , Lars Petersson

3D Gaussian Splatting (3DGS) has become an emerging tool for dynamic scene reconstruction. However, existing methods focus mainly on extending static 3DGS into a time-variant representation, while overlooking the rich motion information…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhiyang Guo , Wengang Zhou , Li Li , Min Wang , Houqiang Li

Neural 3D representations such as Neural Radiance Fields (NeRF), excel at producing photo-realistic rendering results but lack the flexibility for manipulation and editing which is crucial for content creation. Previous works have attempted…

Graphics · Computer Science 2025-03-25 Xiangjun Gao , Xiaoyu Li , Yiyu Zhuang , Qi Zhang , Wenbo Hu , Chaopeng Zhang , Yao Yao , Ying Shan , Long Quan

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

It is vital to infer a signed distance function (SDF) in multi-view based surface reconstruction. 3D Gaussian splatting (3DGS) provides a novel perspective for volume rendering, and shows advantages in rendering efficiency and quality.…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Wenyuan Zhang , Yu-Shen Liu , Zhizhong Han

While 3D Gaussian Splatting (3DGS) excels in static scene modeling, its extension to dynamic scenes introduces significant challenges. Existing dynamic 3DGS methods suffer from either over-smoothing due to low-rank decomposition or feature…

Graphics · Computer Science 2025-08-08 Yifan Zhou , Beizhen Zhao , Pengcheng Wu , Hao Wang

While novel view synthesis (NVS) for dynamic scenes has seen significant progress, reconstructing temporally consistent geometric surfaces remains a challenge. Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) offer powerful…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Minje Kim , Younghyun Noh , Jaesoon Kim , Tae-Kyun Kim

Reconstructing soft tissues from stereo endoscope videos is an essential prerequisite for many medical applications. Previous methods struggle to produce high-quality geometry and appearance due to their inadequate representations of 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Ruyi Zha , Xuelian Cheng , Hongdong Li , Mehrtash Harandi , Zongyuan Ge

We introduce the \method, an ultra-efficient approach for monocular 3D object reconstruction. Splatter Image is based on Gaussian Splatting, which allows fast and high-quality reconstruction of 3D scenes from multiple images. We apply…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Stanislaw Szymanowicz , Christian Rupprecht , Andrea Vedaldi
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