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Related papers: Single-View Rolling-Shutter SfM

200 papers

Rolling shutter (RS) distortion can be interpreted as the result of picking a row of pixels from instant global shutter (GS) frames over time during the exposure of the RS camera. This means that the information of each instant GS frame is…

Computer Vision and Pattern Recognition · Computer Science 2022-07-21 Zhihang Zhong , Mingdeng Cao , Xiao Sun , Zhirong Wu , Zhongyi Zhou , Yinqiang Zheng , Stephen Lin , Imari Sato

In this paper, we tackle the accurate and consistent Structure from Motion (SfM) problem, in particular camera registration, far exceeding the memory of a single computer in parallel. Different from the previous methods which drastically…

Computer Vision and Pattern Recognition · Computer Science 2017-06-06 Siyu Zhu , Tianwei Shen , Lei Zhou , Runze Zhang , Jinglu Wang , Tian Fang , Long Quan

We demonstrate the use of shape-from-shading (SfS) to improve both the quality and the robustness of 3D reconstruction of dynamic objects captured by a single camera. Unlike previous approaches that made use of SfS as a post-processing…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Qi Liu-Yin , Rui Yu , Lourdes Agapito , Andrew Fitzgibbon , Chris Russell

Existing approaches for Structure from Motion (SfM) produce impressive 3-D reconstruction results especially when using imagery captured with large parallax. However, to create engaging video-content in movies and TV shows, the amount by…

Computer Vision and Pattern Recognition · Computer Science 2022-04-07 Sheng Liu , Xiaohan Nie , Raffay Hamid

Structure-from-Motion (SfM) aims to recover 3D scene structures and camera poses based on the correspondences between input images, and thus the ambiguity caused by duplicate structures (i.e., different structures with strong visual…

Computer Vision and Pattern Recognition · Computer Science 2022-06-14 Lei Wang , Linlin Ge , Shan Luo , Zihan Yan , Zhaopeng Cui , Jieqing Feng

Structure-from-Motion (SfM) has become a ubiquitous tool for camera calibration and scene reconstruction with many downstream applications in computer vision and beyond. While the state-of-the-art SfM pipelines have reached a high level of…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Shaohui Liu , Yidan Gao , Tianyi Zhang , Rémi Pautrat , Johannes L. Schönberger , Viktor Larsson , Marc Pollefeys

Most consumer cameras are equipped with electronic rolling shutter, leading to image distortions when the camera moves during image capture. We explore a surprisingly simple camera configuration that makes it possible to undo the rolling…

Computer Vision and Pattern Recognition · Computer Science 2020-06-04 Cenek Albl , Zuzana Kukelova , Viktor Larsson , Tomas Pajdla , Konrad Schindler

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 -- the process of simultaneously estimating camera poses and 3D scene structure from a collection of images -- remains a central challenge in computer vision, with many open problems yet to be solved. Recent advances…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Linfei Pan , Johannes Schönberger , Marc Pollefeys

There has been extensive progress in the reconstruction and generation of 4D scenes from monocular casually-captured video. While these tasks rely heavily on known camera poses, the problem of finding such poses using structure-from-motion…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Lily Goli , Sara Sabour , Mark Matthews , Marcus Brubaker , Dmitry Lagun , Alec Jacobson , David J. Fleet , Saurabh Saxena , Andrea Tagliasacchi

While Structure-from-Motion (SfM) has seen much progress over the years, state-of-the-art systems are prone to failure when facing extreme viewpoint changes in low-overlap, low-parallax or high-symmetry scenarios. Because capturing images…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Zador Pataki , Paul-Edouard Sarlin , Johannes L. Schönberger , Marc Pollefeys

The Structure from Motion (SfM) challenge in computer vision is the process of recovering the 3D structure of a scene from a series of projective measurements that are calculated from a collection of 2D images, taken from different…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Joseph Rowell

Shape-from-Template (SfT) methods estimate 3D surface deformations from a single monocular RGB camera while assuming a 3D state known in advance (a template). This is an important yet challenging problem due to the under-constrained nature…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 Navami Kairanda , Edith Tretschk , Mohamed Elgharib , Christian Theobalt , Vladislav Golyanik

Scene regression methods, such as VGGT, solve the Structure-from-Motion (SfM) problem by directly regressing camera poses and 3D scene structures from input images. They demonstrate impressive performance in handling images under extreme…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Junyuan Deng , Heng Li , Tao Xie , Weiqiang Ren , Qian Zhang , Ping Tan , Xiaoyang Guo

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

Dynamic radiance field reconstruction methods aim to model the time-varying structure and appearance of a dynamic scene. Existing methods, however, assume that accurate camera poses can be reliably estimated by Structure from Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Yu-Lun Liu , Chen Gao , Andreas Meuleman , Hung-Yu Tseng , Ayush Saraf , Changil Kim , Yung-Yu Chuang , Johannes Kopf , Jia-Bin Huang

In this paper, we derive a new differential homography that can account for the scanline-varying camera poses in Rolling Shutter (RS) cameras, and demonstrate its application to carry out RS-aware image stitching and rectification at one…

Computer Vision and Pattern Recognition · Computer Science 2020-08-24 Bingbing Zhuang , Quoc-Huy Tran

The implementation of a Structure-from-Motion (SfM) pipeline from a synthetically generated scene as well as the investigation of the faithfulness of diverse reconstructions is the subject of this project. A series of different SfM…

Computer Vision and Pattern Recognition · Computer Science 2017-10-04 Martin Hahner , Orestis Varesis , Panagiotis Bountouris

We propose a new structure-from-motion framework to recover accurate camera poses and point clouds from unordered images. Traditional SfM systems typically rely on the successful detection of repeatable keypoints across multiple views as…

Computer Vision and Pattern Recognition · Computer Science 2023-06-28 Xingyi He , Jiaming Sun , Yifan Wang , Sida Peng , Qixing Huang , Hujun Bao , Xiaowei Zhou

We propose a framework that extends Blender to exploit Structure from Motion (SfM) and Multi-View Stereo (MVS) techniques for image-based modeling tasks such as sculpting or camera and motion tracking. Applying SfM allows us to determine…

Computer Vision and Pattern Recognition · Computer Science 2021-04-06 Sebastian Bullinger , Christoph Bodensteiner , Michael Arens