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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

Structure from motion is an import theme in computer vision. Although great progress has been made both in theory and applications, most of the algorithms only work for static scenes and rigid objects. In recent years, structure and motion…

Computer Vision and Pattern Recognition · Computer Science 2017-01-02 Guanghui Wang

Structure-from-motion (SfM) is a long-standing problem in the computer vision community, which aims to reconstruct the camera poses and 3D structure of a scene from a set of unconstrained 2D images. Classical frameworks solve this problem…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Jianyuan Wang , Nikita Karaev , Christian Rupprecht , David Novotny

Current non-rigid structure from motion (NRSfM) algorithms are mainly limited with respect to: (i) the number of images, and (ii) the type of shape variability they can handle. This has hampered the practical utility of NRSfM for many…

Computer Vision and Pattern Recognition · Computer Science 2019-08-13 Chen Kong , Simon Lucey

This work addresses the outlier removal problem in large-scale global structure-from-motion. In such applications, global outlier removal is very useful to mitigate the deterioration caused by mismatches in the feature point matching step.…

Computer Vision and Pattern Recognition · Computer Science 2019-02-18 Fei Wen , Danping Zou , Rendong Ying , Peilin Liu

Rigid structure-from-motion (RSfM) and non-rigid structure-from-motion (NRSfM) have long been treated in the literature as separate (different) problems. Inspired by a previous work which solved directly for 3D scene structure by factoring…

Computer Vision and Pattern Recognition · Computer Science 2017-07-18 Pan Ji , Hongdong Li , Yuchao Dai , Ian Reid

Structure from motion (SfM) is an essential computer vision problem which has not been well handled by deep learning. One of the promising trends is to apply explicit structural constraint, e.g. 3D cost volume, into the network. However,…

Computer Vision and Pattern Recognition · Computer Science 2020-08-11 Xingkui Wei , Yinda Zhang , Zhuwen Li , Yanwei Fu , Xiangyang Xue

Image-based 3D reconstruction is one of the most important tasks in Computer Vision with many solutions proposed over the last few decades. The objective is to extract metric information i.e. the geometry of scene objects directly from…

Computer Vision and Pattern Recognition · Computer Science 2022-09-16 Qiao Chen , Charalambos Poullis

Estimating camera intrinsics and extrinsics is a fundamental problem in computer vision, and while advances in structure-from-motion (SfM) have improved accuracy and robustness, open challenges remain. In this paper, we introduce a robust…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Johannes Hägerlind , Bao-Long Tran , Urs Waldmann , Per-Erik Forssén

Structure-from-Motion is a technology used to obtain scene structure through image collection, which is a fundamental problem in computer vision. For unordered Internet images, SfM is very slow due to the lack of prior knowledge about image…

Computer Vision and Pattern Recognition · Computer Science 2023-08-08 Zhichao Ye , Chong Bao , Xin Zhou , Haomin Liu , Hujun Bao , Guofeng Zhang

All current non-rigid structure from motion (NRSfM) algorithms are limited with respect to: (i) the number of images, and (ii) the type of shape variability they can handle. This has hampered the practical utility of NRSfM for many…

Computer Vision and Pattern Recognition · Computer Science 2019-03-01 Chen Kong , Simon Lucey

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

We consider the problem of simultaneously estimating a dense depth map and camera pose for a large set of images of an indoor scene. While classical SfM pipelines rely on a two-step approach where cameras are first estimated using a bundle…

Computer Vision and Pattern Recognition · Computer Science 2020-11-23 Benjamin Graham , David Novotny

Directly regressing the non-rigid shape and camera pose from the individual 2D frame is ill-suited to the Non-Rigid Structure-from-Motion (NRSfM) problem. This frame-by-frame 3D reconstruction pipeline overlooks the inherent…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Hui Deng , Tong Zhang , Yuchao Dai , Jiawei Shi , Yiran Zhong , Hongdong Li

Structure-from-Motion approaches could be broadly divided into two classes: incremental and global. While incremental manner is robust to outliers, it suffers from error accumulation and heavy computation load. The global manner has the…

Computer Vision and Pattern Recognition · Computer Science 2018-03-26 Hainan Cui , Shuhan Shen , Xiang Gao , Zhanyi Hu

We rephrase the problem of 3D reconstruction from images in terms of intersections of projections of orbits of custom built Lie groups actions. We then use an algorithmic method based on moving frames "a la Fels-Olver" to obtain a…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Pierre-Louis Bazin , Mireille Boutin

Multiresolution image fusion is a key problem for real-time satellite imaging and plays a central role in detecting and monitoring natural phenomena such as floods. It aims to solve the trade-off between temporal and spatial resolution in…

Image and Video Processing · Electrical Eng. & Systems 2025-09-17 Haoqing Li , Ricardo Borsoi , Tales Imbiriba , Pau Closas

Structure-from-Motion (SfM), a task aiming at jointly recovering camera poses and 3D geometry of a scene given a set of images, remains a hard problem with still many open challenges despite decades of significant progress. The traditional…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Bardienus Duisterhof , Lojze Zust , Philippe Weinzaepfel , Vincent Leroy , Yohann Cabon , Jerome Revaud

$3$D structure recovery from a collection of $2$D images requires the estimation of the camera locations and orientations, i.e. the camera motion. For large, irregular collections of images, existing methods for the location estimation…

Computer Vision and Pattern Recognition · Computer Science 2015-06-05 Onur Ozyesil , Amit Singer

This paper proposes a new method for Non-Rigid Structure-from-Motion (NRSfM) from a long monocular video sequence observing a non-rigid object performing recurrent and possibly repetitive dynamic action. Departing from the traditional idea…

Computer Vision and Pattern Recognition · Computer Science 2018-04-19 Xiu Li , Hongdong Li , Hanbyul Joo , Yebin Liu , Yaser Sheikh
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