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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

3D Gaussian Splatting (3DGS) has recently emerged as a promising approach in novel view synthesis, combining photorealistic rendering with real-time efficiency. However, its success heavily relies on dense camera coverage; under sparse-view…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiashu Li , Xumeng Han , Zhaoyang Wei , Zipeng Wang , Kuiran Wang , Guorong Li , Zhenjun Han , Jianbin Jiao

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction. However, most existing GS-based surface reconstruction methods focus on 3D objects or limited scenes. Directly applying these methods to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Yuanyuan Gao , Yalun Dai , Hao Li , Weicai Ye , Junyi Chen , Danpeng Chen , Dingwen Zhang , Tong He , Guofeng Zhang , Junwei Han

By adaptively controlling the density and generating more Gaussians in regions with high-frequency information, 3D Gaussian Splatting (3DGS) can better represent scene details. From the signal processing perspective, representing details…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Zhaojie Zeng , Yuesong Wang , Lili Ju , Tao Guan

3D Gaussian Splatting has recently gained traction for its efficient training and real-time rendering. While its vanilla representation is mainly designed for view synthesis, recent works extended it to scene understanding with language…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Siyun Liang , Sen Wang , Kunyi Li , Michael Niemeyer , Stefano Gasperini , Hendrik P. A. Lensch , Nassir Navab , Federico Tombari

4D Gaussian Splatting (4DGS) has recently emerged as a promising technique for capturing complex dynamic 3D scenes with high fidelity. It utilizes a 4D Gaussian representation and a GPU-friendly rasterizer, enabling rapid rendering speeds.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xinjie Zhang , Zhening Liu , Yifan Zhang , Xingtong Ge , Dailan He , Tongda Xu , Yan Wang , Zehong Lin , Shuicheng Yan , Jun Zhang

3D Gaussian Splatting (3DGS) is a leading 3D scene reconstruction method, obtaining high-quality reconstruction with real-time rendering runtime performance. The main idea behind 3DGS is to represent the scene as a collection of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rajaei Khatib , Raja Giryes

We present Real-time Gaussian SLAM (RTG-SLAM), a real-time 3D reconstruction system with an RGBD camera for large-scale environments using Gaussian splatting. The system features a compact Gaussian representation and a highly efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Zhexi Peng , Tianjia Shao , Yong Liu , Jingke Zhou , Yin Yang , Jingdong Wang , Kun Zhou

Although 3D Gaussian Splatting (3D-GS) achieves efficient rendering for novel view synthesis, extending it to dynamic scenes still results in substantial memory overhead from replicating Gaussians across frames. To address this challenge,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chun-Tin Wu , Jun-Cheng Chen

3D Gaussian splatting (3DGS) has enabled various applications in 3D scene representation and novel view synthesis due to its efficient rendering capabilities. However, 3DGS demands relatively significant GPU memory, limiting its use on…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Hengyu Liu , Yuehao Wang , Chenxin Li , Ruisi Cai , Kevin Wang , Wuyang Li , Pavlo Molchanov , Peihao Wang , Zhangyang Wang

Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gaussian Splatting have achieved fine-grained reconstruction and high-fidelity novel view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Yuru Xiao , Zihan Lin , Chao Lu , Deming Zhai , Kui Jiang , Wenbo Zhao , Wei Zhang , Junjun Jiang , Huanran Wang , Xianming Liu

Feed-forward 3D Gaussian Splatting (3DGS) enables efficient one-pass scene reconstruction, providing 3D representations for novel view synthesis without per-scene optimization. However, existing methods typically predict pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Jongmin Park , Minh-Quan Viet Bui , Juan Luis Gonzalez Bello , Jaeho Moon , Jihyong Oh , Munchurl Kim

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

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

Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem. Despite recent advancements, simultaneously achieving high-resolution photorealistic results, real-time rendering, and compact storage remains a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Zhan Li , Zhang Chen , Zhong Li , Yi Xu

Implicit neural representation methods have shown impressive advancements in learning 3D scenes from unstructured in-the-wild photo collections but are still limited by the large computational cost of volumetric rendering. More recently, 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Hiba Dahmani , Moussab Bennehar , Nathan Piasco , Luis Roldao , Dzmitry Tsishkou

Deformable Gaussian Splatting (GS) accomplishes photorealistic dynamic 3-D reconstruction from dense multi-view video (MVV) by learning to deform a canonical GS representation. However, in filmmaking, tight budgets can result in sparse…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Adrian Azzarelli , Nantheera Anantrasirichai , David R Bull

Reconstructing dynamic 3D scenes from monocular videos remains a fundamental challenge in 3D vision. While 3D Gaussian Splatting (3DGS) achieves real-time rendering in static settings, extending it to dynamic scenes is challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Jianing Chen , Zehao Li , Yujun Cai , Hao Jiang , Chengxuan Qian , Juyuan Kang , Shuqin Gao , Honglong Zhao , Tianlu Mao , Yucheng Zhang

As 3D Gaussian Splatting (3DGS) gains popularity as a 3D representation of real scenes, enabling user-friendly deformation to create novel scenes while preserving fine details from the original 3DGS has attracted significant research…

Graphics · Computer Science 2025-04-18 Yifei Tong , Runze Tian , Xiao Han , Dingyao Liu , Fenggen Yu , Yan Zhang

High-quality reconstruction is crucial for dense SLAM. Recent popular approaches utilize 3D Gaussian Splatting (3D GS) techniques for RGB, depth, and semantic reconstruction of scenes. However, these methods often overlook issues of detail…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Zhenzhong Cao , Chenyang Zhao , Qianyi Zhang , Jinzheng Guang , Yinuo Song Jingtai Liu
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