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Related papers: GeoSplatting: Towards Geometry Guided Gaussian Spl…

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Recently, 3D Gaussian Splatting (3DGS) has revolutionized radiance field reconstruction, manifesting efficient and high-fidelity novel view synthesis. However, accurately representing surfaces, especially in large and complex scenarios,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Yang Liu , Chuanchen Luo , Zhongkai Mao , Junran Peng , Zhaoxiang 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

Image data captured outdoors often exhibit unbounded scenes and unconstrained, varying lighting conditions, making it challenging to decompose them into geometry, reflectance, and illumination. Recent works have focused on achieving this…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Lianjun Liao , Chunhui Zhang , Tong Wu , Henglei Lv , Bailin Deng , Lin Gao

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

Recently, 3D Gaussian Splatting has emerged as a prominent research direction owing to its ultrarapid training speed and high-fidelity rendering capabilities. However, the unstructured and irregular nature of Gaussian point clouds poses…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Xiao Ren , Yu Liu , Ning An , Jian Cheng , Xin Qiao , He Kong

Gaussian Splatting (GS) has emerged as an effective representation for photorealistic rendering, but the underlying geometry, material, and lighting remain entangled, hindering scene editing. Existing GS-based methods struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Kang Du , Zhihao Liang , Yulin Shen , Zeyu Wang

The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Traditional methods relying on dense point clouds and triangular meshes struggle with moving…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peizhen Zheng , Dongjing Jiang , Qingchong Jiao , Redouane EL Bouchtaoui , Flynnwell Jianfei Zhang

Decomposing geometry, materials and lighting from a set of images, namely inverse rendering, has been a long-standing problem in computer vision and graphics. Recent advances in neural rendering enable photo-realistic and plausible inverse…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Silong Yong , Venkata Nagarjun Pudureddiyur Manivannan , Bernhard Kerbl , Zifu Wan , Simon Stepputtis , Katia Sycara , Yaqi Xie

The 3D Gaussian Splatting technique has significantly advanced the construction of radiance fields from multi-view images, enabling real-time rendering. While point-based rasterization effectively reduces computational demands for…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Jiaze Li , Zhengyu Wen , Luo Zhang , Jiangbei Hu , Fei Hou , Zhebin Zhang , Ying He

This paper presents a novel system designed for 3D mapping and visual relocalization using 3D Gaussian Splatting. Our proposed method uses LiDAR and camera data to create accurate and visually plausible representations of the environment.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Peng Jiang , Gaurav Pandey , Srikanth Saripalli

Mapping and localization are crucial problems in robotics and autonomous driving. Recent advances in 3D Gaussian Splatting (3DGS) have enabled precise 3D mapping and scene understanding by rendering photo-realistic images. However, existing…

Robotics · Computer Science 2025-01-24 Jaewon Lee , Mangyu Kong , Minseong Park , Euntai Kim

3D Gaussian Splatting (3DGS) has recently attracted wide attentions in various areas such as 3D navigation, Virtual Reality (VR) and 3D simulation, due to its photorealistic and efficient rendering performance. High-quality reconstrution of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Hanqing Jiang , Xiaojun Xiang , Han Sun , Hongjie Li , Liyang Zhou , Xiaoyu Zhang , Guofeng Zhang

Accurate 3D reconstruction of dynamic surgical scenes from endoscopic video is essential for robotic-assisted surgery. While recent 3D Gaussian Splatting methods have shown promise in achieving high-quality reconstructions with fast…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jialei Chen , Xin Zhang , Mobarakol Islam , Francisco Vasconcelos , Danail Stoyanov , Daniel S. Elson , Baoru Huang

We propose GS-IR, a novel inverse rendering approach based on 3D Gaussian Splatting (GS) that leverages forward mapping volume rendering to achieve photorealistic novel view synthesis and relighting results. Unlike previous works that use…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Zhihao Liang , Qi Zhang , Ying Feng , Ying Shan , Kui Jia

3D Gaussian Splatting (3DGS) has recently emerged as a fast, high-quality method for novel view synthesis (NVS). However, its use of low-degree spherical harmonics limits its ability to capture spatially varying color and view-dependent…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hoang Chuong Nguyen , Wei Mao , Jose M. Alvarez , Miaomiao Liu

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xuanqi Zhang , Jieun Lee , Chris Joslin , Wonsook Lee

Virtual production (VP) use LED walls to provide both background imagery and image-based lighting. While this enables on-set compositing, it couples lighting to background and scene appearance, limiting flexibility for downstream editing.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Adrian Azzarelli , Nantheera Anantrasirichai , James Pollock , David R. Bull

In this paper, we present a novel differentiable point-based rendering framework to achieve photo-realistic relighting. To make the reconstructed scene relightable, we enhance vanilla 3D Gaussians by associating extra properties, including…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Jian Gao , Chun Gu , Youtian Lin , Zhihao Li , Hao Zhu , Xun Cao , Li Zhang , Yao Yao

3D Gaussian Splatting has shown remarkable capabilities in novel view rendering tasks and exhibits significant potential for multi-view optimization.However, the original 3D Gaussian Splatting lacks color representation for inputs in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Haoran Wang , Jingwei Huang , Lu Yang , Tianchen Deng , Gaojing Zhang , Mingrui Li

3D modeling of highly reflective objects remains challenging due to strong view-dependent appearances. While previous SDF-based methods can recover high-quality meshes, they are often time-consuming and tend to produce over-smoothed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jinguang Tong , Xuesong li , Fahira Afzal Maken , Sundaram Muthu , Lars Petersson , Chuong Nguyen , Hongdong Li