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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

Structure from Motion (SfM) techniques are being increasingly used to create 3D maps from images in many domains including environmental monitoring. However, SfM techniques are often confounded in visually repetitive environments as they…

Robotics · Computer Science 2022-01-11 Brian M. Hopkinson , Suchendra M. Bhandarkar

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

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 (SfM) often fails to estimate accurate poses in environments that lack suitable visual features. In such cases, the quality of the final 3D mesh, which is contingent on the accuracy of those estimates, is reduced. One…

Computer Vision and Pattern Recognition · Computer Science 2021-04-08 Victor Amblard , Timothy P. Osedach , Arnaud Croux , Andrew Speck , John J. Leonard

Real-time 3D reconstruction of surgical scenes plays a vital role in computer-assisted surgery, holding a promise to enhance surgeons' visibility. Recent advancements in 3D Gaussian Splatting (3DGS) have shown great potential for real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Jiaxin Guo , Jiangliu Wang , Di Kang , Wenzhen Dong , Wenting Wang , Yun-hui Liu

Image retrieval is a critical step for reducing the quadratic cost of image matching in unconstrained Structure-from-Motion (SfM). Unlike generic image retrieval, however, the relevant goal of SfM is to identify geometrically matchable…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Xulei Shi , Maoyu Wang , Yuning Peng , Guanbo Wang , Xin Wang , Yifan Liao , Qi Chen , Pengjie Tao

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

Many monocular visual SLAM algorithms are derived from incremental structure-from-motion (SfM) methods. This work proposes a novel monocular SLAM method which integrates recent advances made in global SfM. In particular, we present two main…

Computer Vision and Pattern Recognition · Computer Science 2017-10-20 Chengzhou Tang , Oliver Wang , Ping Tan

Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effective only in quasi-static scenes, or fail to model 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Qianqian Wang , Vickie Ye , Hang Gao , Weijia Zeng , Jake Austin , Zhengqi Li , Angjoo Kanazawa

Reconstructing 3D shapes from a sequence of images has long been a problem of interest in computer vision. Classical Structure from Motion (SfM) methods have attempted to solve this problem through projected point displacement \& bundle…

Computer Vision and Pattern Recognition · Computer Science 2017-11-07 Rui Zhu , Chaoyang Wang , Chen-Hsuan Lin , Ziyan Wang , Simon Lucey

3D reconstruction of dynamic scenes is a long-standing problem in computer graphics and increasingly difficult the less information is available. Shape-from-Template (SfT) methods aim to reconstruct a template-based geometry from RGB images…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 David Stotko , Nils Wandel , Reinhard Klein

3D reconstruction, which aims to recover the dense three-dimensional structure of a scene, is a cornerstone technology for numerous applications, including augmented/virtual reality, autonomous driving, and robotics. While traditional…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Wei Zhang , Yihang Wu , Songhua Li , Wenjie Ma , Xin Ma , Qiang Li , Qi Wang

Reconstructing and understanding 3D structures from a limited number of images is a well-established problem in computer vision. Traditional methods usually break this task into multiple subtasks, each requiring complex transformations…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Zhiwen Fan , Jian Zhang , Wenyan Cong , Peihao Wang , Renjie Li , Kairun Wen , Shijie Zhou , Achuta Kadambi , Zhangyang Wang , Danfei Xu , Boris Ivanovic , Marco Pavone , Yue Wang

3D reconstruction plays an increasingly important role in modern photogrammetric systems. Conventional satellite or aerial-based remote sensing (RS) platforms can provide the necessary data sources for the 3D reconstruction of large-scale…

Computer Vision and Pattern Recognition · Computer Science 2023-05-19 San Jiang , Yaxin Li , Duojie Weng , Kan You , Wu Chen

We revisit scene-level 3D object detection as the output of an object-centric framework capable of both localization and mapping using 3D oriented boxes as the underlying geometric primitive. While existing 3D object detection approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Justin Lazarow , Kai Kang , Afshin Dehghan

Shape-from-Template (SfT) refers to the class of methods that reconstruct the 3D shape of a deforming object from images/videos using a 3D template. Traditional SfT methods require point correspondences between images and the texture of the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Thuy Tran , Ruochen Chen , Shaifali Parashar

We present a novel 3D mapping pipeline for large-scale indoor environments. To address the significant challenges in large-scale indoor scenes, such as prevalent occlusions and textureless regions, we propose IM360, a novel approach that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Dongki Jung , Jaehoon Choi , Yonghan Lee , Dinesh Manocha

Although numerous solutions have been proposed for image super-resolution, they are usually incompatible with low-power devices with many computational and memory constraints. In this paper, we address this problem by proposing a simple yet…

Computer Vision and Pattern Recognition · Computer Science 2023-02-28 Long Sun , Jiangxin Dong , Jinhui Tang , Jinshan Pan

Image Matching is a core component of all best-performing algorithms and pipelines in 3D vision. Yet despite matching being fundamentally a 3D problem, intrinsically linked to camera pose and scene geometry, it is typically treated as a 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-17 Vincent Leroy , Yohann Cabon , Jérôme Revaud
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