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3D Gaussian Splatting (3D-GS) has recently attracted great attention with real-time and photo-realistic renderings. This technique typically takes perspective images as input and optimizes a set of 3D elliptical Gaussians by splatting them…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Jiayang Bai , Letian Huang , Jie Guo , Wen Gong , Yuanqi Li , Yanwen Guo

Novel view synthesis from limited observations remains an important and persistent task. However, high efficiency in existing NeRF-based few-shot view synthesis is often compromised to obtain an accurate 3D representation. To address this…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Zehao Zhu , Zhiwen Fan , Yifan Jiang , Zhangyang Wang

Sparse-view satellite image surface reconstruction remains highly challenging, fundamentally because the reliability of multi-view matching under satellite imaging conditions is strongly spatially heterogeneous. Affected by large…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Min Chen , Wei Guo , Bin Wang , Wen Li , Tong Fang , Jinbo Zhang , Junqi Zhao , Hong Kuang , Han Hu , Xuming Ge , Qing Zhu , Bo Xu

Recently, Gaussian Splatting, a method that represents a 3D scene as a collection of Gaussian distributions, has gained significant attention in addressing the task of novel view synthesis. In this paper, we highlight a fundamental…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Haoxuan Qu , Zhuoling Li , Hossein Rahmani , Yujun Cai , Jun Liu

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

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

Simultaneous localization and mapping is essential for position tracking and scene understanding. 3D Gaussian-based map representations enable photorealistic reconstruction and real-time rendering of scenes using multiple posed cameras. We…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Lisong C. Sun , Neel P. Bhatt , Jonathan C. Liu , Zhiwen Fan , Zhangyang Wang , Todd E. Humphreys , Ufuk Topcu

Image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of an object or scene from a set of input images. Learning-based methods have gained attention for their ability to directly estimate 3D shapes. This…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Anurag Dalal , Daniel Hagen , Kjell G. Robbersmyr , Kristian Muri Knausgård

Reconstructing a 3D scene from images is challenging due to the different ways light interacts with surfaces depending on the viewer's position and the surface's material. In classical computer graphics, materials can be classified as…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Mateusz Nowak , Wojciech Jarosz , Peter Chin

Efficient scene representations are essential for many real-world applications, especially those involving spatial measurement. Although current NeRF-based methods have achieved impressive results in reconstructing building-scale scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Jianlin Guo , Haihong Xiao , Wenxiong Kang

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

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

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Otto Seiskari , Jerry Ylilammi , Valtteri Kaatrasalo , Pekka Rantalankila , Matias Turkulainen , Juho Kannala , Esa Rahtu , Arno Solin

3D Gaussian Splatting has garnered extensive attention and application in real-time neural rendering. Concurrently, concerns have been raised about the limitations of this technology in aspects such as point cloud storage, performance, and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Letian Huang , Jiayang Bai , Jie Guo , Yuanqi Li , Yanwen Guo

Reconstructing large-scale urban scenes from sparse aerial views is a crucial yet challenging task. Due to biased top-down and shallow-oblique camera poses, sparse aerial captures exhibit strong evidence imbalance: roofs and open regions…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Dongli Wu , Zhuoxiao Li , Tongyan Hua , Yinrui Ren , Xiaobao Wei , Rongjun Qin , Wufan Zhao

We introduce abstract rendering, a method for computing a set of images by rendering a scene from a continuously varying range of camera positions. The resulting abstract image-which encodes an infinite collection of possible renderings-is…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Yangge Li , Chenxi Ji , Xiangru Zhong , Huan Zhang , Sayan Mitra

Recent advancements in 3D Gaussian Splatting (3D-GS) have revolutionized novel view synthesis, facilitating real-time, high-quality image rendering. However, in scenarios involving reflective surfaces, particularly mirrors, 3D-GS often…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Zihan Wang , Shuzhe Wang , Matias Turkulainen , Junyuan Fang , Juho Kannala

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang
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