English
Related papers

Related papers: 2D-SuGaR: Surface-Aware Gaussian Splatting for Geo…

200 papers

While Gaussian Splatting (GS) demonstrates efficient and high-quality scene rendering and small area surface extraction ability, it falls short in handling large-scale aerial image surface extraction tasks. To overcome this, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Zhuoxiao Li , Shanliang Yao , Taoyu Wu , Yong Yue , Wufan Zhao , Rongjun Qin , Angel F. Garcia-Fernandez , Andrew Levers , Xiaohui Zhu

3D Gaussian Splatting (3DGS) has recently emerged in computer vision as a promising rendering technique. By adapting the principles of Elliptical Weighted Average (EWA) splatting to a modern differentiable pipeline, 3DGS enables real-time,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Ling Chen , Bao Yang

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

3D Gaussian Splatting (3DGS) has demonstrated remarkable performance in scene synthesis and novel view synthesis tasks. Typically, the initialization of 3D Gaussian primitives relies on point clouds derived from Structure-from-Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Shan Chen , Jiale Zhou , Lei Li

3D Gaussian Splatting (3DGS) has emerged as a powerful approach for 3D scene reconstruction using 3D Gaussians. However, neither the centers nor surfaces of the Gaussians are accurately aligned to the object surface, complicating their…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Miriam Jäger , Markus Hillemann , Boris Jutzi

3D Gaussian Splatting is crucial for real-time novel view synthesis due to its efficiency and ability to render photorealistic images. However, building a 3D Gaussian is guided solely by photometric loss, which can result in inconsistencies…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Quan Tran , Tuan Dang

Gaussian Splatting (GS) has demonstrated impressive quality and efficiency in novel view synthesis. However, shape extraction from Gaussian primitives remains an open problem. Due to inadequate geometry parameterization and approximation,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Baowen Zhang , Chenxing Jiang , Heng Li , Shaojie Shen , Ping Tan

Neural rendering techniques have made substantial progress in generating photo-realistic 3D scenes. The latest 3D Gaussian Splatting technique has achieved high quality novel view synthesis as well as fast rendering speed. However, 3D…

Graphics · Computer Science 2025-05-09 Xinran Yang , Donghao Ji , Yuanqi Li , Jie Guo , Yanwen Guo , Junyuan Xie

We propose a material-aware optimization framework for high-fidelity mesh reconstruction from multi-view images based on 3D Gaussian Splatting, referred to as GS-2M. Previous works handle these tasks separately and struggle to reconstruct…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Dinh Minh Nguyen , Malte Avenhaus , Thomas Lindemeier

Novel view synthesis (NVS) and surface reconstruction (SR) are essential tasks in 3D Gaussian Splatting (3D-GS). Despite recent progress, these tasks are often addressed independently, with GS-based rendering methods struggling under…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Qingyuan Zhou , Yuehu Gong , Weidong Yang , Jiaze Li , Yeqi Luo , Baixin Xu , Shuhao Li , Ben Fei , Ying He

Using accurate depth priors in 3D Gaussian Splatting helps mitigate artifacts caused by sparse training data and textureless surfaces. However, acquiring accurate depth maps requires specialized acquisition systems. Foundation monocular…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Wenhui Xiao , Ethan Goan , Rodrigo Santa Cruz , David Ahmedt-Aristizabal , Olivier Salvado , Clinton Fookes , Leo Lebrat

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

Recently, Gaussian Splatting (GS) has shown great potential for urban scene reconstruction in the field of autonomous driving. However, current urban scene reconstruction methods often depend on multimodal sensors as inputs, \textit{i.e.}…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Kejing Xia , Jidong Jia , Ke Jin , Yucai Bai , Li Sun , Dacheng Tao , Youjian Zhang

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

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

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

3D Gaussian Splatting (3DGS) is a powerful alternative to Neural Radiance Fields (NeRF), excelling in complex scene reconstruction and efficient rendering. However, it relies on high-quality point clouds from Structure-from-Motion (SfM),…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Ziao Liu , Zhenjia Li , Yifeng Shi , Xiangang Li

Recent years have witnessed the rapid emergence of 3D Gaussian splatting (3DGS) as a powerful approach for 3D reconstruction and novel view synthesis. Its explicit representation with Gaussian primitives enables fast training, real-time…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Haato Watanabe , Nobuyuki Umetani

Reconstructing deformable tissues from endoscopic videos is essential in many downstream surgical applications. However, existing methods suffer from slow rendering speed, greatly limiting their practical use. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Yifan Liu , Chenxin Li , Chen Yang , Yixuan Yuan

We introduce an image upscaling technique tailored for 3D Gaussian Splatting (3DGS) on lightweight GPUs. Compared to 3DGS, it achieves significantly higher rendering speeds and reduces artifacts commonly observed in 3DGS reconstructions.…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Simon Niedermayr , Christoph Neuhauser Rüdiger Westermann
‹ Prev 1 3 4 5 6 7 10 Next ›