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Related papers: SGSST: Scaling Gaussian Splatting StyleTransfer

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Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yaniv Wolf , Amit Bracha , Ron Kimmel

3D Gaussian Splatting (3DGS) has revolutionized neural rendering with its efficiency and quality, but like many novel view synthesis methods, it heavily depends on accurate camera poses from Structure-from-Motion (SfM) systems. Although…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhisheng Huang , Peng Wang , Jingdong Zhang , Yuan Liu , Xin Li , Wenping Wang

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

In this paper, we introduce \textbf{GS-SLAM} that first utilizes 3D Gaussian representation in the Simultaneous Localization and Mapping (SLAM) system. It facilitates a better balance between efficiency and accuracy. Compared to recent SLAM…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Chi Yan , Delin Qu , Dan Xu , Bin Zhao , Zhigang Wang , Dong Wang , Xuelong Li

3D Gaussians have recently emerged as a highly efficient representation for 3D reconstruction and rendering. Despite its high rendering quality and speed at high resolutions, they both deteriorate drastically when rendered at lower…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zhiwen Yan , Weng Fei Low , Yu Chen , Gim Hee Lee

3D style transfer refers to the artistic stylization of 3D assets based on reference style images. Recently, 3DGS-based stylization methods have drawn considerable attention, primarily due to their markedly enhanced training and rendering…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yian Zhao , Rushi Ye , Ruochong Zheng , Zesen Cheng , Chaoran Feng , Jiashu Yang , Pengchong Qiao , Chang Liu , Jie Chen

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

Gaussian Splatting (GS) is a novel, state-of-the-art technique for rendering points in a 3D scene by approximating their contribution to image pixels through Gaussian distributions, warranting fast training and real-time rendering. The main…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Joanna Waczyńska , Piotr Borycki , Sławomir Tadeja , Jacek Tabor , Przemysław Spurek

3D Gaussian splatting video (3DGS) streaming has recently emerged as a research hotspot in both academia and industry, owing to its impressive ability to deliver immersive 3D video experiences. However, research in this area is still in its…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Han Gong , Qiyue Li , Jie Li , Zhi Liu

Recently, 3D Gaussian splatting has gained attention for its capability to generate high-fidelity rendering results. At the same time, most applications such as games, animation, and AR/VR use mesh-based representations to represent and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Jaehoon Choi , Yonghan Lee , Hyungtae Lee , Heesung Kwon , Dinesh Manocha

In this work, we present a novel level-of-detail (LOD) method for 3D Gaussian Splatting that enables real-time rendering of large-scale scenes on memory-constrained devices. Our approach introduces a hierarchical LOD representation that…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Jonas Kulhanek , Marie-Julie Rakotosaona , Fabian Manhardt , Christina Tsalicoglou , Michael Niemeyer , Torsten Sattler , Songyou Peng , Federico Tombari

Recent progress in feed-forward 3D Gaussian Splatting (3DGS) has notably improved rendering quality. However, the spatially uniform and highly redundant 3DGS map generated by previous feed-forward 3DGS methods limits their integration into…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Zicheng Zhang , Xiangting Meng , Ke Wu , Wenchao Ding

Recently, the 3D Gaussian Splatting (3D-GS) method has achieved great success in novel view synthesis, providing real-time rendering while ensuring high-quality rendering results. However, this method faces challenges in modeling specular…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Zhiru Wang , Shiyun Xie , Chengwei Pan , Guoping Wang

This study addresses the challenge of online 3D model generation for neural rendering using an RGB image stream. Previous research has tackled this issue by incorporating Neural Radiance Fields (NeRF) or 3D Gaussian Splatting (3DGS) as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Byeonggwon Lee , Junkyu Park , Khang Truong Giang , Sungho Jo , Soohwan Song

3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limited scenes. In this paper, we make the first attempt to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Junyi Chen , Weicai Ye , Yifan Wang , Danpeng Chen , Di Huang , Wanli Ouyang , Guofeng Zhang , Yu Qiao , Tong He

Despite the advancements in quality and efficiency achieved by 3D Gaussian Splatting (3DGS) in 3D scene rendering, aliasing artifacts remain a persistent challenge. Existing approaches primarily rely on low-pass filtering to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhenya Yang , Bingchen Gong , Kai Chen

The recent advances in 3D Gaussian Splatting (3DGS) show promising results on the novel view synthesis (NVS) task. With its superior rendering performance and high-fidelity rendering quality, 3DGS is excelling at its previous NeRF…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yu Chen , Gim Hee Lee

3D Gaussian Splatting (3DGS) has emerged as a transformative method in the field of real-time novel synthesis. Based on 3DGS, recent advancements cope with large-scale scenes via spatial-based partition strategy to reduce video memory and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-06 Tengfei Wang , Xin Wang , Yongmao Hou , Yiwei Xu , Wendi Zhang , Zongqian Zhan

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

3D Gaussian Splatting is a novel method for 3D view synthesis, which can gain an implicit neural learning rendering result than the traditional neural rendering technology but keep the more high-definition fast rendering speed. But it is…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinwei Lin