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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

Low-light 3D reconstruction from sparse views remains challenging due to exposure imbalance and degraded color fidelity. While existing methods struggle with view inconsistency and require per-scene training, we propose SplatBright, which…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Yue Wen , Liang Song , Hesheng Wang

3D Gaussian Splatting has recently achieved notable success in novel view synthesis for dynamic scenes and geometry reconstruction in static scenes. Building on these advancements, early methods have been developed for dynamic surface…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Decai Chen , Brianne Oberson , Ingo Feldmann , Oliver Schreer , Anna Hilsmann , Peter Eisert

In this work, we present Fed3DGS, a scalable 3D reconstruction framework based on 3D Gaussian splatting (3DGS) with federated learning. Existing city-scale reconstruction methods typically adopt a centralized approach, which gathers all…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Teppei Suzuki

In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate 3D reconstruction with intricate details while inheriting the high efficiency and rendering…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Xiaoyang Lyu , Yang-Tian Sun , Yi-Hua Huang , Xiuzhe Wu , Ziyi Yang , Yilun Chen , Jiangmiao Pang , Xiaojuan Qi

Large-scale 3D reconstruction is critical in the field of robotics, and the potential of 3D Gaussian Splatting (3DGS) for achieving accurate object-level reconstruction has been demonstrated. However, ensuring geometric accuracy in outdoor…

Robotics · Computer Science 2024-09-20 Changjian Jiang , Ruilan Gao , Kele Shao , Yue Wang , Rong Xiong , Yu Zhang

3D Gaussian Splatting (3DGS) has emerged as a prominent technique with the potential to become a mainstream method for 3D representations. It can effectively transform multi-view images into explicit 3D Gaussian through efficient training,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Yanqi Bao , Tianyu Ding , Jing Huo , Yaoli Liu , Yuxin Li , Wenbin Li , Yang Gao , Jiebo Luo

Articulated objects are ubiquitous in daily environments, and their 3D reconstruction holds great significance across various fields. However, existing articulated object reconstruction methods typically require costly inputs such as…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Di Wu , Liu Liu , Xueyu Yuan , Wenxiao Chen , Lijun Yue , Liuzhu Chen , Yiming Tang , Meng Wang

3D Gaussian Splatting (3DGS) is a leading 3D scene reconstruction method, obtaining high-quality reconstruction with real-time rendering runtime performance. The main idea behind 3DGS is to represent the scene as a collection of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rajaei Khatib , Raja Giryes

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

While 3D Gaussian Splatting (3DGS) has revolutionized real-time photorealistic view synthesis, its fundamental reliance on symmetric Gaussian distributions introduces visual artifacts that hinder accurate spatial data exploration.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Beizhen Zhao , Yifan Zhou , Gaochao Song , Ziran Yin , Hao Wang

3D Gaussian Splatting (3DGS) represents a significant advancement in the field of efficient and high-fidelity novel view synthesis. Despite recent progress, achieving accurate geometric reconstruction under sparse-view conditions remains a…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Zexu Huang , Min Xu , Stuart Perry

3D Gaussian Splatting (3DGS) has revolutionized 3D scene reconstruction, which effectively balances rendering quality, efficiency, and speed. However, existing 3DGS approaches usually generate plausible outputs and face significant…

Graphics · Computer Science 2025-07-22 Beizhen Zhao , Yifan Zhou , Sicheng Yu , Zijian Wang , Hao Wang

3D Gaussian splatting (3DGS) has demonstrated impressive performance in synthesizing high-fidelity novel views. Nonetheless, its effectiveness critically depends on the quality of the initialized point cloud. Specifically, achieving uniform…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yikang Zhang , Rui Fan

We present GauStudio, a novel modular framework for modeling 3D Gaussian Splatting (3DGS) to provide standardized, plug-and-play components for users to easily customize and implement a 3DGS pipeline. Supported by our framework, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Chongjie Ye , Yinyu Nie , Jiahao Chang , Yuantao Chen , Yihao Zhi , Xiaoguang Han

Multi-view mesh reconstruction remains a core challenge in computer graphics and vision, especially for recovering high-frequency geometry from sparse observations. Recent methods such as 3D Gaussian Splatting (3DGS) and Neural Radiance…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Nandhana Sunil , Abhirami R Iyer , Avirup Mandal

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

Recently, the integration of the efficient feed-forward scheme into 3D Gaussian Splatting (3DGS) has been actively explored. However, most existing methods focus on sparse view reconstruction of small regions and cannot produce eligible…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

3D Gaussian Splatting (3DGS) has shown remarkable performance in novel view synthesis. However, its rendering quality deteriorates with sparse inphut views, leading to distorted content and reduced details. This limitation hinders its…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Zongqi He , Zhe Xiao , Kin-Chung Chan , Yushen Zuo , Jun Xiao , Kin-Man Lam

3D Gaussian Splatting (3DGS) has gained significant attention for its high-quality rendering capabilities, ultra-fast training, and inference speeds. However, when we apply 3DGS to surface reconstruction tasks, especially in environments…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Chenfeng Hou , Qi Xun Yeo , Mengqi Guo , Yongxin Su , Yanyan Li , Gim Hee Lee