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Related papers: MotionGS : Compact Gaussian Splatting SLAM by Moti…

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Recent works in volume rendering, \textit{e.g.} NeRF and 3D Gaussian Splatting (3DGS), significantly advance the rendering quality and efficiency with the help of the learned implicit neural radiance field or 3D Gaussians. Rendering on top…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Xiaobiao Du , Yida Wang , Xin Yu

We introduce Go-SLAM, a novel framework that utilizes 3D Gaussian Splatting SLAM to reconstruct dynamic environments while embedding object-level information within the scene representations. This framework employs advanced object…

Robotics · Computer Science 2024-09-26 Phu Pham , Dipam Patel , Damon Conover , Aniket Bera

We propose the first 4D tracking and mapping method that jointly performs camera localization and non-rigid surface reconstruction via differentiable rendering. Our approach captures 4D scenes from an online stream of color images with…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Hidenobu Matsuki , Gwangbin Bae , Andrew J. Davison

Recently, Gaussian splatting has emerged as a strong alternative to NeRF, demonstrating impressive 3D modeling capabilities while requiring only a fraction of the training and rendering time. In this paper, we show how the standard Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Luca Savant Aira , Gabriele Facciolo , Thibaud Ehret

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

3D Gaussian Splatting (3DGS) has enabled the creation of highly realistic 3D scene representations from sets of multi-view images. However, inpainting missing regions, whether due to occlusion or scene editing, remains a challenging task,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-10 Mahtab Dahaghin , Milind G. Padalkar , Matteo Toso , Alessio Del Bue

In recent years, there have been significant advancements in 3D reconstruction and dense RGB-D SLAM systems. One notable development is the application of Neural Radiance Fields (NeRF) in these systems, which utilizes implicit neural…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Tianchen Deng , Yanbo Wang , Hongle Xie , Hesheng Wang , Jingchuan Wang , Danwei Wang , Weidong Chen

We leverage repetitive elements in 3D scenes to improve novel view synthesis. Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have greatly improved novel view synthesis but renderings of unseen and occluded parts remain…

Dynamic scene reconstruction poses a persistent challenge in 3D vision. Deformable 3D Gaussian Splatting has emerged as an effective method for this task, offering real-time rendering and high visual fidelity. This approach decomposes a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Bing He , Yunuo Chen , Guo Lu , Qi Wang , Qunshan Gu , Rong Xie , Li Song , Wenjun Zhang

3D Gaussian Splatting (3DGS) proposes an efficient solution for novel view synthesis. Its framework provides fast and high-fidelity rendering. Although less complex than other solutions such as Neural Radiance Fields (NeRF), there are still…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Stéphane Pateux , Matthieu Gendrin , Luce Morin , Théo Ladune , Xiaoran Jiang

Accurate 3D reconstruction of dynamic surgical scenes from endoscopic video is essential for robotic-assisted surgery. While recent 3D Gaussian Splatting methods have shown promise in achieving high-quality reconstructions with fast…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jialei Chen , Xin Zhang , Mobarakol Islam , Francisco Vasconcelos , Danail Stoyanov , Daniel S. Elson , Baoru Huang

In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Wenkai Liu , Tao Guan , Bin Zhu , Lili Ju , Zikai Song , Dan Li , Yuesong Wang , Wei Yang

Modeling complex rigid motion across large spatiotemporal spans remains an unresolved challenge in dynamic reconstruction. Existing paradigms are mainly confined to short-term, small-scale deformation and offer limited consideration for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Yijun Xu , Jingrui Zhang , Yuhan Chen , Dingwen Wang , Lei Yu , Chu He

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

Recent advances in neural radiation fields (NeRF) and 3D Gaussian-based SLAM have achieved impressive localization accuracy and high-quality dense mapping in static scenes. However, these methods remain challenged in dynamic environments,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Wenhua Wu , Chenpeng Su , Siting Zhu , Tianchen Deng , Jianhao Jiao , Guangming Wang , Dimitrios Kanoulas , Zhe Liu , Hesheng Wang

While neural rendering has demonstrated impressive capabilities in 3D scene reconstruction and novel view synthesis, it heavily relies on high-quality sharp images and accurate camera poses. Numerous approaches have been proposed to train…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Lingzhe Zhao , Peng Wang , Peidong Liu

Incrementally recovering real-sized 3D geometry from a pose-free RGB stream is a challenging task in 3D reconstruction, requiring minimal assumptions on input data. Existing methods can be broadly categorized into end-to-end and visual…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Linqing Zhao , Xiuwei Xu , Yirui Wang , Hao Wang , Wenzhao Zheng , Yansong Tang , Haibin Yan , Jiwen Lu

Monocular SLAM has received a lot of attention due to its simple RGB inputs and the lifting of complex sensor constraints. However, existing monocular SLAM systems are designed for bounded scenes, restricting the applicability of SLAM…

Computer Vision and Pattern Recognition · Computer Science 2024-03-11 Heng Zhou , Zhetao Guo , Shuhong Liu , Lechen Zhang , Qihao Wang , Yuxiang Ren , Mingrui Li

Combining accurate geometry with rich semantics has been proven to be highly effective for language-guided robotic manipulation. Existing methods for dynamic scenes either fail to update in real-time or rely on additional depth sensors for…

Robotics · Computer Science 2024-10-22 Yu Sheng , Runfeng Lin , Lidian Wang , Quecheng Qiu , YanYong Zhang , Yu Zhang , Bei Hua , Jianmin Ji

Mobile robots and IoT devices demand real-time localization and dense reconstruction under tight compute and energy budgets. While 3D Gaussian Splatting (3DGS) enables efficient dense SLAM, dynamic objects and occlusions still degrade…

Robotics · Computer Science 2026-03-02 Li Zhang , Yu-An Liu , Xijia Jiang , Conghao Huang , Danyang Li , Yanyong Zhang
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