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Reconstructing the 3D shape of a deformable environment from the information captured by a moving depth camera is highly relevant to surgery. The underlying challenge is the fact that simultaneously estimating camera motion and tissue…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Guido Caccianiga , Julian Nubert , Cesar Cadena , Marco Hutter , Katherine J. Kuchenbecker

Structure-from-Motion (SfM) is a fundamental 3D vision task for recovering camera parameters and scene geometry from multi-view images. While recent deep learning advances enable accurate Monocular Depth Estimation (MDE) from single images…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Shengjie Zhu , Ahmed Abdelkader , Mark J. Matthews , Xiaoming Liu , Wen-Sheng Chu

This paper presents a neural incremental Structure-from-Motion (SfM) approach, Level-S$^2$fM, which estimates the camera poses and scene geometry from a set of uncalibrated images by learning coordinate MLPs for the implicit surfaces and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Yuxi Xiao , Nan Xue , Tianfu Wu , Gui-Song Xia

The primary contribution of this paper is an efficient Structure from Motion (SfM) solution for oblique unmanned aerial vehicle (UAV) images. First, an algorithm, considering spatial relationship constrains between image footprints, is…

Computer Vision and Pattern Recognition · Computer Science 2017-05-10 San Jiang , Wanshou Jiang

We address rotation averaging (RA) and its application to real-world 3D reconstruction. Local optimisation based approaches are the de facto choice, though they only guarantee a local optimum. Global optimisers ensure global optimality in…

Computer Vision and Pattern Recognition · Computer Science 2021-03-30 Yu Chen , Ji Zhao , Laurent Kneip

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 perspective camera and the isometric surface prior have recently gathered increased attention for Non-Rigid Structure-from-Motion (NRSfM). Despite the recent progress, several challenges remain, particularly the computational complexity…

Computer Vision and Pattern Recognition · Computer Science 2018-08-14 Thomas Probst , Danda Pani Paudel , Ajad Chhatkuli , Luc Van Gool

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

This work introduces an effective and practical solution to the dense two-view structure from motion (SfM) problem. One vital question addressed is how to mindfully use per-pixel optical flow correspondence between two frames for accurate…

Computer Vision and Pattern Recognition · Computer Science 2023-02-14 Weirong Chen , Suryansh Kumar , Fisher Yu

Structure from Motion (SfM) refers to the problem of recovering both structure (i.e., 3D coordinates of points in the scene) and motion (i.e., camera matrices) starting from point correspondences in multiple images. It has attracted…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Federica Arrigoni

Creating accurate and efficient 3D models poses significant challenges, particularly in addressing large viewpoint variations, computational complexity, and alignment discrepancies. Efficient camera path generation can help resolve these…

Computer Vision and Pattern Recognition · Computer Science 2025-05-26 Usha Kumari , Shuvendu Rana

Two-view structure-from-motion (SfM) is the cornerstone of 3D reconstruction and visual SLAM. Existing deep learning-based approaches formulate the problem by either recovering absolute pose scales from two consecutive frames or predicting…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Jianyuan Wang , Yiran Zhong , Yuchao Dai , Stan Birchfield , Kaihao Zhang , Nikolai Smolyanskiy , Hongdong Li

Multi-Camera Multi-Target (MCMT) tracking aims to locate and associate the same targets across multiple camera views. Existing methods typically adopt a two-stage framework, involving single-camera tracking followed by inter-camera…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yihao Zhen , Mingyue Xu , Qiang Wang , Baojie Fan , Jiahua Dong , Tinghui Zhao , Huijie Fan

Over the last decades, ample achievements have been made on Structure from motion (SfM). However, the vast majority of them basically work in an offline manner, i.e., images are firstly captured and then fed together into a SfM pipeline for…

Computer Vision and Pattern Recognition · Computer Science 2024-02-15 Zongqian Zhan , Rui Xia , Yifei Yu , Yibo Xu , Xin Wang

Transformers have revolutionized deep learning based computer vision with improved performance as well as robustness to natural corruptions and adversarial attacks. Transformers are used predominantly for 2D vision tasks, including image…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Hemang Chawla , Arnav Varma , Elahe Arani , Bahram Zonooz

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

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

3D Gaussian Splatting (3DGS) has demonstrated remarkable real-time performance in novel view synthesis, yet its effectiveness relies heavily on dense multi-view inputs with precisely known camera poses, which are rarely available in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zongqi He , Hanmin Li , Kin-Chung Chan , Yushen Zuo , Hao Xie , Zhe Xiao , Jun Xiao , Kin-Man Lam

World-wide detailed 2D maps require enormous collective efforts. OpenStreetMap is the result of 11 million registered users manually annotating the GPS location of over 1.75 billion entries, including distinctive landmarks and common urban…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Matteo Toso , Stefano Fiorini , Stuart James , Alessio Del Bue

Although Structure-from-Motion (SfM) as a maturing technique has been widely used in many applications, state-of-the-art SfM algorithms are still not robust enough in certain situations. For example, images for inspection purposes are often…

Robotics · Computer Science 2019-11-11 Weikun Zhen , Yaoyu Hu , Huai Yu , Sebastian Scherer