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3D Gaussian Splatting has emerged as a very promising scene representation, achieving state-of-the-art quality in novel view synthesis significantly faster than competing alternatives. However, its use of spherical harmonics to represent…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 T. Berriel Martins , Javier Civera

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

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 (3DGS) achieves high-fidelity rendering with fast real-time performance, but existing methods rely on offline training after full Structure-from-Motion (SfM) processing. In contrast, this work introduces Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Yiwei Xu , Yifei Yu , Wentian Gan , Tengfei Wang , Zongqian Zhan , Hao Cheng , Xin Wang

We present 3DGS-CD, the first 3D Gaussian Splatting (3DGS)-based method for detecting physical object rearrangements in 3D scenes. Our approach estimates 3D object-level changes by comparing two sets of unaligned images taken at different…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Ziqi Lu , Jianbo Ye , John Leonard

Combining 3D Gaussian splatting with Simultaneous Localization and Mapping (SLAM) has gained popularity as it enables continuous 3D environment reconstruction during motion. However, existing methods struggle in dynamic environments,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yangfan Zhao , Hanwei Zhang , Ke Huang , Qiufeng Wang , Zhenzhou Shao , Dengyu Wu

Recently, 3D Gaussian Splatting (3DGS) has emerged as a significant advancement in 3D scene reconstruction, attracting considerable attention due to its ability to recover high-fidelity details while maintaining low complexity. Despite the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Qiqi Hou , Randall Rauwendaal , Zifeng Li , Hoang Le , Farzad Farhadzadeh , Fatih Porikli , Alexei Bourd , Amir Said

3D Gaussian Splatting (3DGS) has emerged as a promising representation for photorealistic rendering of 3D scenes. However, its high storage requirements pose significant challenges for practical applications. We observe that Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2025-11-05 Yuang Shi , Simone Gasparini , Géraldine Morin , Chenggang Yang , Wei Tsang Ooi

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis results while advancing real-time rendering performance. However, it relies heavily on the quality of the initial point cloud, resulting in blurring and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zheng Zhang , Wenbo Hu , Yixing Lao , Tong He , Hengshuang Zhao

The introduction of 3D Gaussian Splatting (3DGS) has advanced novel view synthesis by utilizing Gaussians to represent scenes. Encoding Gaussian point features with anchor embeddings has significantly enhanced the performance of newer 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Junyan Su , Baozhu Zhao , Xiaohan Zhang , Qi Liu

Open-vocabulary 3D scene understanding presents a significant challenge in computer vision, with wide-ranging applications in embodied agents and augmented reality systems. Existing methods adopt neurel rendering methods as 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Jun Guo , Xiaojian Ma , Yue Fan , Huaping Liu , Qing Li

3D Gaussian Splatting has shown remarkable capabilities in novel view rendering tasks and exhibits significant potential for multi-view optimization.However, the original 3D Gaussian Splatting lacks color representation for inputs in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Haoran Wang , Jingwei Huang , Lu Yang , Tianchen Deng , Gaojing Zhang , Mingrui Li

As an emerging novel view synthesis approach, 3D Gaussian Splatting (3DGS) demonstrates fast training/rendering with superior visual quality. The two tasks of 3DGS, Gaussian creation and view rendering, are typically separated over time or…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Yuning Huang , Jiahao Pang , Fengqing Zhu , Dong Tian

3D Gaussian Splatting (3DGS) is a major breakthrough in 3D scene reconstruction. With a number of views of a given object or scene, the algorithm trains a model composed of 3D gaussians, which enables the production of novel views from…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Matthieu Gendrin , Stéphane Pateux , Théo Ladune

3D Gaussian Splatting (3DGS) has become one of the most influential works in the past year. Due to its efficient and high-quality novel view synthesis capabilities, it has been widely adopted in many research fields and applications.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Glenn Grubert , Florian Barthel , Anna Hilsmann , Peter Eisert

Recent advancements in multi-view 3D reconstruction and novel-view synthesis, particularly through Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have greatly enhanced the fidelity and efficiency of 3D content creation.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Jun Zhou , Dinghao Li , Nannan Li , Mingjie Wang

3D Gaussian Splatting (3DGS) enables efficient rendering, yet accurate surface reconstruction remains challenging due to unreliable geometric supervision. Existing approaches predominantly rely on depth-based reprojection to infer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Mai Su , Qihan Yu , Zhongtao Wang , Yilong Li , Chengwei Pan , Yisong Chen , Guoping Wang , Fei Zhu

Neural rendering methods have significantly advanced photo-realistic 3D scene rendering in various academic and industrial applications. The recent 3D Gaussian Splatting method has achieved the state-of-the-art rendering quality and speed…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Tao Lu , Mulin Yu , Linning Xu , Yuanbo Xiangli , Limin Wang , Dahua Lin , Bo Dai

This work presents a novel pipeline to recover the 3D structure of an unknown target spacecraft from a sequence of images captured during Rendezvous and Proximity Operations (RPO) in space. The target's geometry and appearance are…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Tae Ha Park , Simone D'Amico

Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the solution space. For example, one pixel in the first frame might…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Junhao He , Jiaxu Wang , Jia Li , Mingyuan Sun , Qiang Zhang , Jiahang Cao , Ziyi Zhang , Yi Gu , Jingkai Sun , Renjing Xu