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Manual modeling of material parameters and 3D geometry is a time consuming yet essential task in the gaming and film industries. While recent advances in 3D reconstruction have enabled accurate approximations of scene geometry and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Philipp Langsteiner , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

3D Gaussian Splatting (3DGS) has recently emerged as a fast, high-quality method for novel view synthesis (NVS). However, its use of low-degree spherical harmonics limits its ability to capture spatially varying color and view-dependent…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hoang Chuong Nguyen , Wei Mao , Jose M. Alvarez , Miaomiao Liu

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

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

We present LocoGS, a locality-aware 3D Gaussian Splatting (3DGS) framework that exploits the spatial coherence of 3D Gaussians for compact modeling of volumetric scenes. To this end, we first analyze the local coherence of 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Seungjoo Shin , Jaesik Park , Sunghyun Cho

3D Gaussian splatting (3DGS) is an innovative rendering technique that surpasses the neural radiance field (NeRF) in both rendering speed and visual quality by leveraging an explicit 3D scene representation. Existing 3DGS approaches require…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Lintao Xiang , Hongpei Zheng , Yating Huang , Qijun Yang , Hujun Yin

High-fidelity reconstruction of deformable tissues from endoscopic videos remains challenging due to the limitations of existing methods in capturing subtle color variations and modeling global deformations. While 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Qun Ji , Peng Li , Mingqiang Wei

While 3D Gaussian Splatting (3DGS) enables real-time rendering, its training demands workstation-level compute and memory, making mobile deployment impractical under minute-scale time budgets and limited peak memory. We present PocketGS, a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Wenzhi Guo , Guangchi Fang , Shu Yang , Bing Wang

Visual SLAM algorithms achieve significant improvements through the exploration of 3D Gaussian Splatting (3DGS) representations, particularly in generating high-fidelity dense maps. However, they depend on a static environment assumption…

Robotics · Computer Science 2026-04-15 Yi Liu , Haoxuan Xu , Hongbo Duan , Keyu Fan , Zhengyang Zhang , Peiyu Zhuang , Pengting Luo , Houde Liu

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Danpeng Chen , Hai Li , Weicai Ye , Yifan Wang , Weijian Xie , Shangjin Zhai , Nan Wang , Haomin Liu , Hujun Bao , Guofeng Zhang

3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of the prior and representation do not involve novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Junoh Lee , Chang-Yeon Won , Hyunjun Jung , Inhwan Bae , Hae-Gon Jeon

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

Probabilistic graphical models (PGMs) serve as a powerful framework for modeling complex systems with uncertainty and extracting valuable insights from data. However, users face challenges when applying PGMs to their problems in terms of…

Machine Learning · Computer Science 2024-05-29 Jiantong Jiang , Zeyi Wen , Peiyu Yang , Atif Mansoor , Ajmal Mian

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

3D Gaussian Splatting (3DGS) allows flexible adjustments to scene representation, enabling continuous optimization of scene quality during dense visual simultaneous localization and mapping (SLAM) in static environments. However, 3DGS faces…

Robotics · Computer Science 2024-11-26 Long Wen , Shixin Li , Yu Zhang , Yuhong Huang , Jianjie Lin , Fengjunjie Pan , Zhenshan Bing , Alois Knoll

3D Gaussian Splatting (3DGS) has begun incorporating rich information from 2D foundation models. However, most approaches rely on a bottom-up optimization process that treats raw 2D features as ground truth, incurring increased…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Hyunjoon Lee , Joonkyu Min , Jaesik Park

Novel-view synthesis plays a crucial role in computer vision with applications in 3D reconstruction, mixed reality, and robotics. Recent approaches, such as 3D Gaussian Splatting (3DGS), have emerged as state-of-the-art solutions, offering…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Ankit Dhiman , Tao Lu , R Srinath , Emre Arslan , Angela Xing , Yuanbo Xiangli , R Venkatesh Babu , Srinath Sridhar

Scene understanding based on 3D Gaussian Splatting (3DGS) has recently achieved notable advances. Although 3DGS related methods have efficient rendering capabilities, they fail to address the inherent contradiction between the anisotropic…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Q. G. Duan , Benyun Zhao , Mingqiao Han Yijun Huang , Ben M. Chen

3D Gaussian Splatting (3DGS) has made significant strides in scene representation and neural rendering, with intense efforts focused on adapting it for dynamic scenes. Despite delivering remarkable rendering quality and speed, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sangwoon Kwak , Joonsoo Kim , Jun Young Jeong , Won-Sik Cheong , Jihyong Oh , Munchurl Kim

3D Gaussian Splatting (3DGS) has shown its ability in rapid rendering and high-fidelity mapping. In this paper, we introduce LVI-GS, a tightly-coupled LiDAR-Visual-Inertial mapping framework with 3DGS, which leverages the complementary…

Robotics · Computer Science 2024-11-06 Huibin Zhao , Weipeng Guan , Peng Lu
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