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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

Structure from Motion (SfM) is a critical task in computer vision, aiming to recover the 3D scene structure and camera motion from a sequence of 2D images. The recent pose-only imaging geometry decouples 3D coordinates from camera poses and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Xinrui Li , Qi Cai , Yuanxin Wu

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

This paper introduces a network architecture to solve the structure-from-motion (SfM) problem via feature-metric bundle adjustment (BA), which explicitly enforces multi-view geometry constraints in the form of feature-metric error. The…

Computer Vision and Pattern Recognition · Computer Science 2019-08-27 Chengzhou Tang , Ping Tan

Two-view structure from motion (SfM) is the cornerstone of 3D reconstruction and visual SLAM (vSLAM). Many existing end-to-end learning-based methods usually formulate it as a brute regression problem. However, the inadequate utilization of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-12 Yuxi Xiao , Li Li , Xiaodi Li , Jian Yao

Non-Rigid Structure-from-Motion (NRSfM) problem aims to recover 3D geometry of a deforming object from its 2D feature correspondences across multiple frames. Classical approaches to this problem assume a small number of feature points and,…

Computer Vision and Pattern Recognition · Computer Science 2020-06-17 Suryansh Kumar , Luc Van Gool , Carlos E. P. de Oliveira , Anoop Cherian , Yuchao Dai , Hongdong Li

We present a novel multi-altitude camera pose estimation system, addressing the challenges of robust and accurate localization across varied altitudes when only considering sparse image input. The system effectively handles diverse…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Yaxuan Li , Yewei Huang , Bijay Gaudel , Hamidreza Jafarnejadsani , Brendan Englot

We consider the problem of reconstructing a 3-D scene from a moving camera with high frame rate using the affine projection model. This problem is traditionally known as Affine Structure from Motion (Affine SfM), and can be solved using an…

Computer Vision and Pattern Recognition · Computer Science 2016-08-10 Roberto Tron

We present VGGT, a feed-forward neural network that directly infers all key 3D attributes of a scene, including camera parameters, point maps, depth maps, and 3D point tracks, from one, a few, or hundreds of its views. This approach is a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Jianyuan Wang , Minghao Chen , Nikita Karaev , Andrea Vedaldi , Christian Rupprecht , David Novotny

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

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

Image matching, which establishes correspondences between two-view images to recover 3D structure and camera geometry, serves as a cornerstone in computer vision and underpins a wide range of applications, including visual localization, 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Shihua Zhang , Zizhuo Li , Kaining Zhang , Yifan Lu , Yuxin Deng , Linfeng Tang , Xingyu Jiang , Jiayi Ma

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

Reconstructing high-quality 3D models from sparse 2D images has garnered significant attention in computer vision. Recently, 3D Gaussian Splatting (3DGS) has gained prominence due to its explicit representation with efficient training speed…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Keng-Wei Chang , Zi-Ming Wang , Shang-Hong Lai

This article describes a technique to augment a typical RGBD sensor by integrating depth estimates obtained via Structure-from-Motion (SfM) with sensor depth measurements. Limitations in the RGBD depth sensing technology prevent capturing…

Computer Vision and Pattern Recognition · Computer Science 2021-03-12 Akash Chandrashekar , John Papadakis , Andrew Willis , Jamie Gantert

Reliable displacement measurement is fundamental for structural health monitoring and digital engineering workflows, as it provides direct structural response information. Vision-based measurement has emerged as a promising approach for…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Qingyu Xian , Hao Cheng , Berend Jan van der Zwaag , Rolands Kromanis , Ozlem Durmaz Incel

We propose SfM-Net, a geometry-aware neural network for motion estimation in videos that decomposes frame-to-frame pixel motion in terms of scene and object depth, camera motion and 3D object rotations and translations. Given a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2017-04-26 Sudheendra Vijayanarasimhan , Susanna Ricco , Cordelia Schmid , Rahul Sukthankar , Katerina Fragkiadaki

Despite the impressive results achieved by many existing Structure from Motion (SfM) approaches, there is still a need to improve the robustness, accuracy, and efficiency on large-scale scenes with many outlier matches and sparse view…

Computer Vision and Pattern Recognition · Computer Science 2023-01-31 Yu Chen , Zihao Yu , Shu Song , Tianning Yu , Jianming Li , Gim Hee Lee

We introduce a comprehensive benchmark for local features and robust estimation algorithms, focusing on the downstream task -- the accuracy of the reconstructed camera pose -- as our primary metric. Our pipeline's modular structure allows…

Computer Vision and Pattern Recognition · Computer Science 2021-02-12 Yuhe Jin , Dmytro Mishkin , Anastasiia Mishchuk , Jiri Matas , Pascal Fua , Kwang Moo Yi , Eduard Trulls

Creating 3D models through the Structure from Motion technique is a recognized, efficient, cost-effective structural monitoring strategy. This technique is applied in several engineering fields, particularly for creating models of large…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Francisco Roza de Moraes , Irineu da Silva