English
Related papers

Related papers: G-Style: Stylized Gaussian Splatting

200 papers

Recent advances in 3D Gaussian Splatting have shown remarkable potential for novel view synthesis. However, most existing large-scale scene reconstruction methods rely on the divide-and-conquer paradigm, which often leads to the loss of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Chuandong Liu , Huijiao Wang , Lei Yu , Gui-Song Xia

Gaussian Splatting has recently become one of the most popular frameworks for photorealistic 3D scene reconstruction and rendering. While current rasterizers allow for efficient mappings of 3D Gaussian splats onto 2D camera views, this work…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Daniel Lieber , Alexander Mock , Nils Wandel

Scene reconstruction has emerged as a central challenge in computer vision, with approaches such as Neural Radiance Fields (NeRF) and Gaussian Splatting achieving remarkable progress. While Gaussian Splatting demonstrates strong performance…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Alexander Valverde , Brian Xu , Yuyin Zhou , Meng Xu , Hongyun Wang

We present FPGS, a feed-forward photorealistic style transfer method of large-scale radiance fields represented by Gaussian Splatting. FPGS, stylizes large-scale 3D scenes with arbitrary, multiple style reference images without additional…

Graphics · Computer Science 2025-03-14 GeonU Kim , Kim Youwang , Lee Hyoseok , Tae-Hyun Oh

Gaussian splatting methods are emerging as a popular approach for converting multi-view image data into scene representations that allow view synthesis. In particular, there is interest in enabling view synthesis for dynamic scenes using…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yiqing Liang , Mikhail Okunev , Mikaela Angelina Uy , Runfeng Li , Leonidas Guibas , James Tompkin , Adam W. Harley

3D Gaussian Splatting has shown impressive novel view synthesis results; nonetheless, it is vulnerable to dynamic objects polluting the input data of an otherwise static scene, so called distractors. Distractors have severe impact on the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Paul Ungermann , Armin Ettenhofer , Matthias Nießner , Barbara Roessle

Traditional SLAM algorithms excel at camera tracking, but typically produce incomplete and low-resolution maps that are not tightly integrated with semantics prediction. Recent work integrates Gaussian Splatting (GS) into SLAM to enable…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Mingqi Jiang , Chanho Kim , Chen Ziwen , Li Fuxin

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

3D Gaussian Splatting (3DGS) has revolutionized high-fidelity neural rendering with its explicit representation and efficiency. However, reconstructing scenes from sparse viewpoints suffers from severe geometric voids and floaters due to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Ao Gao , Jingyu Gong , Xin Tan , Zhizhong Zhang , Lizhuang Ma , Yuan Xie

High-quality novel view synthesis for large-scale scenes presents a challenging dilemma in 3D computer vision. Existing methods typically partition large scenes into multiple regions, reconstruct a 3D representation using Gaussian splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Xiaohan Zhang , Sitong Wang , Yushen Yan , Yi Yang , Mingda Xu , Qi Liu

3D Gaussian Splatting (3DGS) enables efficient reconstruction and high-fidelity real-time rendering of complex scenes on consumer hardware. However, due to its rasterization-based formulation, 3DGS is constrained to ideal pinhole cameras…

Graphics · Computer Science 2025-03-26 Qi Wu , Janick Martinez Esturo , Ashkan Mirzaei , Nicolas Moenne-Loccoz , Zan Gojcic

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

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

Semantic-aware 3D scene reconstruction is essential for autonomous robots to perform complex interactions. Semantic SLAM, an online approach, integrates pose tracking, geometric reconstruction, and semantic mapping into a unified framework,…

Robotics · Computer Science 2025-05-20 Zuxing Lu , Xin Yuan , Shaowen Yang , Jingyu Liu , Changyin Sun

Recent work has shown that 3D Gaussian-based SLAM enables high-quality reconstruction, accurate pose estimation, and real-time rendering of scenes. However, these approaches are built on a tremendous number of redundant 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Tianchen Deng , Chang Nie , Shuhong Liu , Wenhua Wu , Jianfei Yang , Shenghai Yuan , Jiuming Liu , Danwei Wang , Hesheng Wang

This paper tackles the intricate challenge of object removal to update the radiance field using the 3D Gaussian Splatting. The main challenges of this task lie in the preservation of geometric consistency and the maintenance of texture…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Yuxin Wang , Qianyi Wu , Guofeng Zhang , Dan Xu

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

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

The creation of digital replicas of physical objects has valuable applications for the preservation and dissemination of tangible cultural heritage. However, existing methods are often slow, expensive, and require expert knowledge. We…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Mahtab Dahaghin , Myrna Castillo , Kourosh Riahidehkordi , Matteo Toso , Alessio Del Bue

Text-to-3D, known for its efficient generation methods and expansive creative potential, has garnered significant attention in the AIGC domain. However, the pixel-wise rendering of NeRF and its ray marching light sampling constrain the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Xinhai Li , Huaibin Wang , Kuo-Kun Tseng