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3D Gaussian Splatting reconstructs scenes by starting from a sparse Structure-from-Motion initialization and refining under-reconstructed regions. This process is slow, as it requires multiple densification steps where Gaussians are…

Graphics · Computer Science 2026-02-13 Dmytro Kotovenko , Olga Grebenkova , Björn Ommer

In this paper, we propose an end-to-end transcoding pipeline, to create 3D Gaussian splatting (3DGS) models from existing 3D plenoptic point cloud or mesh models, when the original multi-view images of the captured 3D object or scene are…

Image and Video Processing · Electrical Eng. & Systems 2026-05-21 Maja Krivokuća , Riad Bendouro , Neus Sabater

Recent advancements in neural rendering, particularly 2D Gaussian Splatting (2DGS), have shown promising results for jointly reconstructing fine appearance and geometry by leveraging 2D Gaussian surfels. However, current methods face…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Yunzhou Song , Heguang Lin , Jiahui Lei , Lingjie Liu , Kostas Daniilidis

3D Gaussian Splatting (3DGS) has demonstrated its advantages in achieving fast and high-quality rendering. As point clouds serve as a widely-used and easily accessible form of 3D representation, bridging the gap between point clouds and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Wenyuan Zhang , Yu-Shen Liu

Sparse-view scene reconstruction often faces significant challenges due to the constraints imposed by limited observational data. These limitations result in incomplete information, leading to suboptimal reconstructions using existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Xiangyu Sun , Runnan Chen , Mingming Gong , Dong Xu , Tongliang Liu

Differentiable 3D-Gaussian splatting (GS) is emerging as a prominent technique in computer vision and graphics for reconstructing 3D scenes. GS represents a scene as a set of 3D Gaussians with varying opacities and employs a computationally…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Ziyuan Qu , Omkar Vengurlekar , Mohamad Qadri , Kevin Zhang , Michael Kaess , Christopher Metzler , Suren Jayasuriya , Adithya Pediredla

In recent years, Neural Radiance Fields (NeRF) has revolutionized three-dimensional (3D) reconstruction with its implicit representation. Building upon NeRF, 3D Gaussian Splatting (3D-GS) has departed from the implicit representation of…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Bin Zhang , Bi Zeng , Zexin Peng

We introduce StyleGaussian, a novel 3D style transfer technique that allows instant transfer of any image's style to a 3D scene at 10 frames per second (fps). Leveraging 3D Gaussian Splatting (3DGS), StyleGaussian achieves style transfer…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Kunhao Liu , Fangneng Zhan , Muyu Xu , Christian Theobalt , Ling Shao , Shijian Lu

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

Endoluminal endoscopic procedures are essential for diagnosing colorectal cancer and other severe conditions in the digestive tract, urogenital system, and airways. 3D reconstruction and novel-view synthesis from endoscopic images are…

Maintaining consistent 3D scene representations over time is a significant challenge in computer vision. Updating 3D scenes from sparse-view observations is crucial for various real-world applications, including urban planning, disaster…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Zeyuan An , Yanghang Xiao , Zhiying Leng , Frederick W. B. Li , Xiaohui Liang

In this paper, we aim ambitiously for a realistic yet challenging problem, namely, how to reconstruct high-quality 3D scenes from sparse low-resolution views that simultaneously suffer from deficient perspectives and clarity. Whereas…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Yecong Wan , Mingwen Shao , Yuanshuo Cheng , Wangmeng Zuo

Recent advancements in 3D reconstruction coupled with neural rendering techniques have greatly improved the creation of photo-realistic 3D scenes, influencing both academic research and industry applications. The technique of 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Zexu Huang , Min Xu , Stuart Perry

We introduce LighthouseGS, a practical novel view synthesis framework based on 3D Gaussian Splatting that utilizes simple panorama-style captures from a single mobile device. While convenient, this rotation-dominant motion and narrow…

Graphics · Computer Science 2026-02-12 Seungoh Han , Jaehoon Jang , Hyunsu Kim , Jaeheung Surh , Junhyung Kwak , Hyowon Ha , Kyungdon Joo

Point cloud registration is a fundamental problem for large-scale 3D scene scanning and reconstruction. With the help of deep learning, registration methods have evolved significantly, reaching a nearly-mature stage. As the introduction of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Jiahao Chang , Yinglin Xu , Yihao Li , Yuantao Chen , Xiaoguang Han

We introduce GaussianCut, a new method for interactive multiview segmentation of scenes represented as 3D Gaussians. Our approach allows for selecting the objects to be segmented by interacting with a single view. It accepts intuitive user…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Umangi Jain , Ashkan Mirzaei , Igor Gilitschenski

3D Gaussian Splatting (GS) has emerged as a powerful representation for high-quality scene reconstruction, offering compelling rendering quality. However, the training process of GS often suffers from slow convergence due to inefficient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Binxiao Huang , Zhengwu Liu , Ngai Wong

3D head animation has seen major quality and runtime improvements over the last few years, particularly empowered by the advances in differentiable rendering and neural radiance fields. Real-time rendering is a highly desirable goal for…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Helisa Dhamo , Yinyu Nie , Arthur Moreau , Jifei Song , Richard Shaw , Yiren Zhou , Eduardo Pérez-Pellitero

Recent advances in 3D Gaussian Splatting (3DGS) deliver striking photorealism, and extending it to large scenes opens new opportunities for semantic reasoning and prediction in applications such as autonomous driving. Today's…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Shengkai Zhang , Yuhe Liu , Jianhua He , Xuedou Xiao , Mozi Chen , Kezhong Liu

This paper presents a multimodal framework that integrates touch signals (contact points and surface normals) into 3D Gaussian Splatting (3DGS). Our approach enhances scene reconstruction, particularly under challenging conditions like low…

Signal Processing · Electrical Eng. & Systems 2025-08-12 Yuchen Gao , Xiao Xu , Eckehard Steinbach , Daniel E. Lucani , Qi Zhang
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