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Non-Rigid Structure from Motion (NRSfM) refers to the problem of reconstructing cameras and the 3D point cloud of a non-rigid object from an ensemble of images with 2D correspondences. Current NRSfM algorithms are limited from two…

Computer Vision and Pattern Recognition · Computer Science 2019-09-10 Chen Kong , Simon Lucey

The integration of aerial and ground images has been a promising solution in 3D modeling of complex scenes, which is seriously restricted by finding reliable correspondences. The primary contribution of this study is a feature matching…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Jiangxue Yu , Hui Wang , San Jiang , Xing Zhang , Dejin Zhang , Qingquan Li

Finding local features that are repeatable across multiple views is a cornerstone of sparse 3D reconstruction. The classical image matching paradigm detects keypoints per-image once and for all, which can yield poorly-localized features and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Philipp Lindenberger , Paul-Edouard Sarlin , Viktor Larsson , Marc Pollefeys

In this paper, we address the inverse problem of reconstructing a scene as well as the camera motion from the image sequence taken by an omni-directional camera. Our structure from motion results give sharp conditions under which the…

Computer Vision and Pattern Recognition · Computer Science 2007-08-21 Oliver Knill , Jose Ramirez-Herran

Single-pixel imaging (SPI) is significant for applications constrained by transmission bandwidth or lighting band, where 3D SPI can be further realized through capturing signals carrying depth. Sampling strategy and reconstruction algorithm…

Image and Video Processing · Electrical Eng. & Systems 2025-04-01 Xinyue Ma , Chenxing Wang

Despite impressive results achieved by many on-land visual mapping algorithms in the recent decades, transferring these methods from land to the deep sea remains a challenge due to harsh environmental conditions. Images captured by…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Mengkun She , Yifan Song , David Nakath , Kevin Köser

3D face reconstruction (3DFR) algorithms are based on specific assumptions tailored to distinct application scenarios. These assumptions limit their use when acquisition conditions, such as the subject's distance from the camera or the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Simone Maurizio La Cava , Sara Concas , Ruben Tolosana , Roberto Casula , Giulia Orrù , Martin Drahansky , Julian Fierrez , Gian Luca Marcialis

Recent advances in neural reconstruction enable high-quality 3D object reconstruction from casually captured image collections. Current techniques mostly analyze their progress on relatively simple image collections where…

3D phenotyping of plants plays a crucial role for understanding plant growth, yield prediction, and disease control. We present a pipeline capable of generating high-quality 3D reconstructions of individual agricultural plants. To acquire…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Andre Rochow , Jonas Marcic , Svetlana Seliunina , Sven Behnke

City-scale 3D reconstruction from satellite imagery presents the challenge of extreme viewpoint extrapolation, where our goal is to synthesize ground-level novel views from sparse orbital images with minimal parallax. This requires…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Fei Yu , Yu Liu , Luyang Tang , Mingchao Sun , Zengye Ge , Rui Bu , Yuchao Jin , Haisen Zhao , He Sun , Yangyan Li , Mu Xu , Wenzheng Chen , Baoquan Chen

Structure-from-Motion (SfM) is the task of estimating 3D structure and camera poses from images. We define Collaborative SfM (ColabSfM) as sharing distributed SfM reconstructions. Sharing maps requires estimating a joint reference frame,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Johan Edstedt , André Mateus , Alberto Jaenal

We are working towards 3D reconstruction of indoor spaces using a pair of HDR cameras in a stereo vision configuration mounted on an indoor mobile floor robot that captures various textures and spatial features as 2D images and this data is…

Computer Vision and Pattern Recognition · Computer Science 2023-06-13 Kshitij Karnawat , Hritvik Choudhari , Abhimanyu Saxena , Mudit Singal , Raajith Gadam

3D scene modeling techniques serve as the bedrocks in the geospatial engineering and computer science, which drives many applications ranging from automated driving, terrain mapping, navigation, virtual, augmented, mixed, and extended…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Shuang Song

Super-resolution reconstruction techniques entail the utilization of software algorithms to transform one or more sets of low-resolution images captured from the same scene into high-resolution images. In recent years, considerable…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Hao Yan , Zixiang Wang , Zhengjia Xu , Zhuoyue Wang , Zhizhong Wu , Ranran Lyu

Signed distance functions (SDFs) is an attractive framework that has recently shown promising results for 3D shape reconstruction from images. SDFs seamlessly generalize to different shape resolutions and topologies but lack explicit…

Computer Vision and Pattern Recognition · Computer Science 2023-04-25 Zerui Chen , Shizhe Chen , Cordelia Schmid , Ivan Laptev

We consider the problem of reconstructing a 3-D scene from a moving camera with high frame rate using the affine projection model. This problem is traditionally known as Affine Structure from Motion (Affine SfM), and can be solved using an…

Computer Vision and Pattern Recognition · Computer Science 2016-08-10 Roberto Tron

We present a method to reconstruct the three-dimensional trajectory of a moving instance of a known object category using stereo video data. We track the two-dimensional shape of objects on pixel level exploiting instance-aware semantic…

Computer Vision and Pattern Recognition · Computer Science 2018-08-29 Sebastian Bullinger , Christoph Bodensteiner , Michael Arens , Rainer Stiefelhagen

Reconstructing a 3D scene from unordered images is pivotal in computer vision and robotics, with applications spanning crowd-sourced mapping and beyond. While global Structure-from-Motion (SfM) techniques are scalable and fast, they often…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Linfei Pan , Marc Pollefeys , Dániel Baráth

The creation of detailed 3D models is relevant for a wide range of applications such as navigation in three-dimensional space, construction planning or disaster assessment. However, the complex processing and long execution time for…

Computer Vision and Pattern Recognition · Computer Science 2021-10-25 Max Hermann , Thomas Pollok , Daniel Brommer , Dominic Zahn

Recently, 3D Gaussian Splatting (3DGS) has demonstrated excellent ability in small-scale 3D surface reconstruction. However, extending 3DGS to large-scale scenes remains a significant challenge. To address this gap, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 YuanZheng Wu , Jin Liu , Shunping Ji