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Related papers: Simulating Structure-from-Motion

200 papers

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

Structure from Motion (SfM) estimates camera poses and reconstructs point clouds, forming a foundation for various tasks. However, applying SfM to driving scenes captured by multi-camera systems presents significant difficulties, including…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Lingfeng Xuan , Chang Nie , Yiqing Xu , Zhe Liu , Yanzi Miao , Hesheng Wang

Reconstructing the surfaces of deformable objects from correspondences between a 3D template and a 2D image is well studied under Shape-from-Template (SfT) methods; however, existing approaches break down when topological changes accompany…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Kevin Manogue , Tomasz M Schang , Dilara Kuş , Jonas Müller , Stefan Zachow , Agniva Sengupta

Physics driven image simulation allows for the modeling and creation of realistic imagery beyond what is afforded by typical rendering pipelines. We aim to automatically generate a physically realistic scene for simulation of a given region…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Scott Sorensen , Wayne Treible , Robert Wagner , Andrew D. Gilliam , Todd Rovito , Joseph L. Mundy

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

In this paper, we propose a novel projector-camera system for practical and low-cost acquisition of a dense object 3D model with the spectral reflectance property. In our system, we use a standard RGB camera and leverage an off-the-shelf…

Computer Vision and Pattern Recognition · Computer Science 2019-08-23 Chunyu Li , Yusuke Monno , Hironori Hidaka , Masatoshi Okutomi

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

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

Rolling-shutter (RS) cameras are ubiquitous, but RS SfM (structure-from-motion) has not been fully solved yet. This work suggests an approach to remedy this: We characterize RS single-view geometry of observed world points or lines.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Sofía Errázuriz Muñoz , Kim Kiehn , Petr Hruby , Kathlén Kohn

Recovering the 3D structure of the surrounding environment is an essential task in any vision-controlled Structure-from-Motion (SfM) scheme. This paper focuses on the theoretical properties of the SfM, known as the incremental active depth…

Robotics · Computer Science 2020-03-17 Romulo T. Rodrigues , Pedro Miraldo , Dimos V. Dimarogonas , A. Pedro Aguiar

Infrared thermography has been widely used in several domains to capture and measure temperature distributions across surfaces and objects. This methodology can be further expanded to 3D applications if the spatial distribution of the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Jincheng Zhang , Kevin Brink , Andrew R Willis

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

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

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 present Dense-SfM, a novel Structure from Motion (SfM) framework designed for dense and accurate 3D reconstruction from multi-view images. Sparse keypoint matching, which traditional SfM methods often rely on, limits both accuracy and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 JongMin Lee , Sungjoo Yoo

Lifting Structure-from-Motion (SfM) information from sequential and non-sequential image data is a time-consuming and computationally expensive task. In addition to this, the majority of publicly available data is unfit for processing due…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Sanchit Kaul , Joseph Luna , Shray Arora

We describe a special case of structure from motion where the camera rotates on a sphere. The camera's optical axis lies perpendicular to the sphere's surface. In this case, the camera's pose is minimally represented by three rotation…

Computer Vision and Pattern Recognition · Computer Science 2016-09-06 Jonathan Ventura

Camera pose estimation is a long-standing computer vision problem that to date often relies on classical methods, such as handcrafted keypoint matching, RANSAC and bundle adjustment. In this paper, we propose to formulate the Structure from…

Computer Vision and Pattern Recognition · Computer Science 2024-01-26 Jianyuan Wang , Christian Rupprecht , David Novotny

Shape from Focus (SFF) is a depth reconstruction technique that estimates scene structure from focus variations observed across a focal stack, that is, a sequence of images captured at different focus settings. A key limitation of SFF…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Khurram Ashfaq , Muhammad Tariq Mahmood

Recovering structure and motion parameters given a image pair or a sequence of images is a well studied problem in computer vision. This is often achieved by employing Structure from Motion (SfM) or Simultaneous Localization and Mapping…

Computer Vision and Pattern Recognition · Computer Science 2018-11-07 Thanuja Dharmasiri , Andrew Spek , Tom Drummond