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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

Radiance field-based methods have recently been used to reconstruct human avatars, showing that we can significantly downscale the systems needed for creating animated human avatars. Although this progress has been initiated by neural…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Nikolaos Zioulis , Nikolaos Kotarelas , Georgios Albanis , Spyridon Thermos , Anargyros Chatzitofis

In recent years, 3D Gaussian splatting (3DGS) has achieved remarkable progress in novel view synthesis. However, accurately reconstructing glossy surfaces under complex illumination remains challenging, particularly in scenes with strong…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Ningjing Fan , Yiqun Wang

Differentiable 3D Gaussian splatting has emerged as an efficient and flexible rendering technique for representing complex scenes from a collection of 2D views and enabling high-quality real-time novel-view synthesis. However, its reliance…

Graphics · Computer Science 2025-01-16 Meenakshi Krishnan , Liam Fowl , Ramani Duraiswami

Recently, Gaussian splatting has emerged as a robust technique for representing 3D scenes, enabling real-time rasterization and high-fidelity rendering. However, Gaussians' inherent radial symmetry and smoothness constraints limit their…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yi-Hua Huang , Ming-Xian Lin , Yang-Tian Sun , Ziyi Yang , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

Existing feed-forward 3D Gaussian Splatting methods predict pixel-aligned primitives, leading to a quadratic growth in primitive count as resolution increases. This fundamentally limits their scalability, making high-resolution synthesis…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Yixing Lao , Xuyang Bai , Xiaoyang Wu , Nuoyuan Yan , Zixin Luo , Tian Fang , Jean-Daniel Nahmias , Yanghai Tsin , Shiwei Li , Hengshuang Zhao

Gaussian Splatting has recently emerged as the go-to representation for reconstructing and rendering 3D scenes. The transition from 3D to 2D Gaussian primitives has further improved multi-view consistency and surface reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Sebastian Weiss , Derek Bradley

Recently, high-fidelity scene reconstruction with an optimized 3D Gaussian splat representation has been introduced for novel view synthesis from sparse image sets. Making such representations suitable for applications like network…

Computer Vision and Pattern Recognition · Computer Science 2024-01-23 Simon Niedermayr , Josef Stumpfegger , Rüdiger Westermann

Generalizable 3D Gaussian Splatting has recently emerged as an efficient approach for novel-view synthesis, enabling feed-forward synthesis from only a few input views. However, existing pixel-wise feed-forward methods suffer from…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Hoang Chuong Nguyen , Renjie Wu , Jose M. Alvarez , Miaomiao Liu

Implicit neural representations (INRs) have achieved remarkable success in image representation and compression, but they require substantial training time and memory. Meanwhile, recent 2D Gaussian Splatting (GS) methods (\textit{e.g.},…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Tiantian Li , Xinjie Zhang , Xingtong Ge , Tongda Xu , Dailan He , Jun Zhang , Yan Wang

During the Gaussian Splatting optimization process, the scene's geometry can gradually deteriorate if its structure is not deliberately preserved, especially in non-textured regions such as walls, ceilings, and furniture surfaces. This…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yanyan Li , Chenyu Lyu , Yan Di , Guangyao Zhai , Gim Hee Lee , Federico Tombari

Image-based surface reconstruction and characterization are crucial for missions to small celestial bodies (e.g., asteroids), as it informs mission planning, navigation, and scientific analysis. Recent advances in Gaussian splatting enable…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Jennifer Nolan , Travis Driver , John Christian

Recent advancements in 3D Gaussian Splatting (3D-GS) have revolutionized novel view synthesis, facilitating real-time, high-quality image rendering. However, in scenarios involving reflective surfaces, particularly mirrors, 3D-GS often…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Zihan Wang , Shuzhe Wang , Matias Turkulainen , Junyuan Fang , Juho Kannala

This paper presents Planar Gaussian Splatting (PGS), a novel neural rendering approach to learn the 3D geometry and parse the 3D planes of a scene, directly from multiple RGB images. The PGS leverages Gaussian primitives to model the scene…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Farhad G. Zanjani , Hong Cai , Hanno Ackermann , Leila Mirvakhabova , Fatih Porikli

Gaussian Splatting has emerged as a powerful representation for high-quality, real-time 3D scene rendering. While recent works extend Gaussians with learnable textures to enrich visual appearance, existing approaches allocate a fixed square…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Sheng-Chi Hsu , Ting-Yu Yen , Shih-Hsuan Hung , Hung-Kuo Chu

Scene change detection methods built on Gaussian splatting universally follow a render-then-compare paradigm: the pre-change scene is rendered into 2D and compared against post-change images via pixel or feature residuals. This change…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chamuditha Jayanga Galappaththige , Jason Lai , Timothy Patten , Donald Dansereau , Niko Suenderhauf , Dimity Miller

3D Gaussian splatting provides excellent visual quality for novel view synthesis, with fast training and real-time rendering; unfortunately, the memory requirements of this method for storing and transmission are unreasonably high. We first…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Panagiotis Papantonakis , Georgios Kopanas , Bernhard Kerbl , Alexandre Lanvin , George Drettakis

Reconstructing objects from posed images is a crucial and complex task in computer graphics and computer vision. While NeRF-based neural reconstruction methods have exhibited impressive reconstruction ability, they tend to be…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Shuichang Lai , Letian Huang , Jie Guo , Kai Cheng , Bowen Pan , Xiaoxiao Long , Jiangjing Lyu , Chengfei Lv , Yanwen Guo
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