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This paper presents a neural-network-based solution to recover pixels occluded by clouds in satellite images. We leverage radio frequency (RF) signals in the ultra/super-high frequency band that penetrate clouds to help reconstruct the…

Computer Vision and Pattern Recognition · Computer Science 2021-06-17 Mingmin Zhao , Peder A. Olsen , Ranveer Chandra

A laser scanner can easily acquire the geometric data of physical environments in the form of a point cloud. Recognizing objects from a point cloud is often required for industrial 3D reconstruction, which should include not only geometry…

Computer Vision and Pattern Recognition · Computer Science 2020-07-01 Hyungki Kim , Moohyun Cha , Duhwan Mun

Incremental Structure from Motion (ISfM) has been widely used for UAV image orientation. Its efficiency, however, decreases dramatically due to the sequential constraint. Although the divide-and-conquer strategy has been utilized for…

Computer Vision and Pattern Recognition · Computer Science 2023-02-08 San Jiang , Qingquan Li , Wanshou Jiang , Wu Chen

Currently, numerous remote sensing satellites provide a huge volume of diverse earth observation data. As these data show different features regarding resolution, accuracy, coverage, and spectral imaging ability, fusion techniques are…

Image and Video Processing · Electrical Eng. & Systems 2018-10-29 Hossein Bagheri , Michael Schmitt , Pablo d'Angelo , Xiao Xiang Zhu

Surface reconstruction and novel view rendering from sparse-view images are challenging. Signed Distance Function (SDF)-based methods struggle with fine details, while 3D Gaussian Splatting (3DGS)-based approaches lack global geometry…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Zihui Gao , Jia-Wang Bian , Guosheng Lin , Hao Chen , Chunhua Shen

3D surface reconstruction from point clouds is a key step in areas such as content creation, archaeology, digital cultural heritage, and engineering. Current approaches either try to optimize a non-data-driven surface representation to fit…

Computer Vision and Pattern Recognition · Computer Science 2024-02-09 Philipp Erler , Lizeth Fuentes , Pedro Hermosilla , Paul Guerrero , Renato Pajarola , Michael Wimmer

Structure from Motion (SfM) using imagery that involves extreme appearance changes is yet a challenging task due to a loss of feature repeatability. Using feature correspondences obtained by matching densely extracted convolutional neural…

Computer Vision and Pattern Recognition · Computer Science 2018-05-14 Aji Resindra Widya , Akihiko Torii , Masatoshi Okutomi

This paper presents a multi stage 3D shape reconstruction system of multiple object scenes by considering the silhouette inconsistencies in shape-from silhouette SFS method. These inconsistencies are common in multiple view images due to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-22 Waqqas-ur-Rehman Butt , Martin Servin

Existing deep methods produce highly accurate 3D reconstructions in stereo and multiview stereo settings, i.e., when cameras are both internally and externally calibrated. Nevertheless, the challenge of simultaneous recovery of camera poses…

Computer Vision and Pattern Recognition · Computer Science 2021-10-26 Dror Moran , Hodaya Koslowsky , Yoni Kasten , Haggai Maron , Meirav Galun , Ronen Basri

Image matching, which establishes correspondences between two-view images to recover 3D structure and camera geometry, serves as a cornerstone in computer vision and underpins a wide range of applications, including visual localization, 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Shihua Zhang , Zizhuo Li , Kaining Zhang , Yifan Lu , Yuxin Deng , Linfeng Tang , Xingyu Jiang , Jiayi Ma

State-of-the-art 3D computer vision algorithms continue to advance in handling sparse, unordered image sets. Recently developed foundational models for 3D reconstruction, such as Dense and Unconstrained Stereo 3D Reconstruction (DUSt3R),…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Xinyi Wu , Steven Landgraf , Markus Ulrich , Rongjun Qin

This paper presents a neural incremental Structure-from-Motion (SfM) approach, Level-S$^2$fM, which estimates the camera poses and scene geometry from a set of uncalibrated images by learning coordinate MLPs for the implicit surfaces and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Yuxi Xiao , Nan Xue , Tianfu Wu , Gui-Song Xia

Reconstructing accurate 3D surfaces for street-view scenarios is crucial for applications such as digital entertainment and autonomous driving simulation. However, existing street-view datasets, including KITTI, Waymo, and nuScenes, only…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Yubin Hu , Kairui Wen , Heng Zhou , Xiaoyang Guo , Yong-Jin Liu

In this paper, we address the problem of 3D object mesh reconstruction from RGB videos. Our approach combines the best of multi-view geometric and data-driven methods for 3D reconstruction by optimizing object meshes for multi-view…

Computer Vision and Pattern Recognition · Computer Science 2019-03-21 Chen-Hsuan Lin , Oliver Wang , Bryan C. Russell , Eli Shechtman , Vladimir G. Kim , Matthew Fisher , Simon Lucey

We present a comprehensive survey and benchmark of both traditional and learning-based methods for surface reconstruction from point clouds. This task is particularly challenging for real-world acquisitions due to factors such as noise,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Raphael Sulzer , Renaud Marlet , Bruno Vallet , Loic Landrieu

Contextual information can have a substantial impact on the performance of visual tasks such as semantic segmentation, object detection, and geometric estimation. Data stored in Geographic Information Systems (GIS) offers a rich source of…

Computer Vision and Pattern Recognition · Computer Science 2016-02-22 Raúl Díaz , Minhaeng Lee , Jochen Schubert , Charless C. Fowlkes

A critical step in the digital surface models(DSM) generation is feature matching. Off-track (or multi-date) satellite stereo images, in particular, can challenge the performance of feature matching due to spectral distortions between…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Shuang Song , Luca Morelli , Xinyi Wu , Rongjun Qin , Hessah Albanwan , Fabio Remondino

Gaussian Splatting (GS) has gained attention as a fast and effective method for novel view synthesis. It has also been applied to 3D reconstruction using multi-view images and can achieve fast and accurate 3D reconstruction. However, GS…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Natsuki Takama , Shintaro Ito , Koichi Ito , Hwann-Tzong Chen , Takafumi Aoki

Efficient and accurate 3D reconstruction is crucial for various applications, including augmented and virtual reality, medical imaging, and cinematic special effects. While traditional Multi-View Stereo (MVS) systems have been fundamental…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Umair Haroon , Ahmad AlMughrabi , Ricardo Marques , Petia Radeva

3D reconstruction is a fundamental issue in many applications and the feature point matching problem is a key step while reconstructing target objects. Conventional algorithms can only find a small number of feature points from two images…

Computer Vision and Pattern Recognition · Computer Science 2019-11-26 Zhihao Fang , He Ma , Xuemin Zhu , Xutao Guo , Ruixin Zhou