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Structure-from-Motion (SfM) is a fundamental technique for recovering camera poses and scene structure from multi-view imagery, serving as a critical upstream component for applications ranging from 3D reconstruction to modern neural scene…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Jiankun Zhong , Zitong Zhan , Quankai Gao , Ziyu Chen , Haozhe Lou , Jiageng Mao , Ulrich Neumann , Chen Wang , Yue Wang

Spatially and temporally highly resolved depth information enables numerous applications including human-machine interaction in gaming or safety functions in the automotive industry. In this paper, we address this issue using Time-of-flight…

Numerical Analysis · Mathematics 2018-12-27 Stephan Antholzer , Christoph Wolf , Michael Sandbichler , Markus Dielacher , Markus Haltmeier

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

In recent years, structured matrix recovery problems have gained considerable attention for its real world applications, such as recommender systems and computer vision. Much of the existing work has focused on matrices with low-rank…

Machine Learning · Statistics 2016-04-13 Sheng Chen , Arindam Banerjee

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

The vast majority of Shape-from-Polarization (SfP) methods work under the oversimplified assumption of using orthographic cameras. Indeed, it is still not well understood how to project the Stokes vectors when the incoming rays are not…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Mara Pistellato , Filippo Bergamasco

We introduce a novel learning-based method to reconstruct the high-quality geometry and complex, spatially-varying BRDF of an arbitrary object from a sparse set of only six images captured by wide-baseline cameras under collocated point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-07 Sai Bi , Zexiang Xu , Kalyan Sunkavalli , David Kriegman , Ravi Ramamoorthi

Accurate perception of the vehicle's 3D surroundings, including fine-scale road geometry, such as bumps, slopes, and surface irregularities, is essential for safe and comfortable vehicle control. However, conventional monocular depth…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Gasser Elazab , Maximilian Jansen , Michael Unterreiner , Olaf Hellwich

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

We propose a framework called ReFInE to directly obtain integral image estimates from a very small number of spatially multiplexed measurements of the scene without iterative reconstruction of any auxiliary image, and demonstrate their…

Computer Vision and Pattern Recognition · Computer Science 2016-01-28 Kuldeep Kulkarni , Pavan Turaga

Multiview Structure from Motion is a fundamental and challenging computer vision problem. A recent deep-based approach utilized matrix equivariant architectures for simultaneous recovery of camera pose and 3D scene structure from large…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Fadi Khatib , Yoni Kasten , Dror Moran , Meirav Galun , Ronen Basri

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

A limitation of many compressive imaging architectures lies in the sequential nature of the sensing process, which leads to long sensing times. In this paper we present a novel architecture that uses fewer detectors than the number of…

Computer Vision and Pattern Recognition · Computer Science 2013-11-05 Tomas Björklund , Enrico Magli

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

Fourier domain structured low-rank matrix priors are emerging as powerful alternatives to traditional image recovery methods such as total variation and wavelet regularization. These priors specify that a convolutional structured matrix,…

Numerical Analysis · Computer Science 2017-06-27 Greg Ongie , Mathews Jacob

We present "Humans and Structure from Motion" (HSfM), a method for jointly reconstructing multiple human meshes, scene point clouds, and camera parameters in a metric world coordinate system from a sparse set of uncalibrated multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Lea Müller , Hongsuk Choi , Anthony Zhang , Brent Yi , Jitendra Malik , Angjoo Kanazawa

We completely classify all minimal problems for Structure-from-Motion (SfM) where arrangements of points and lines are fully observed by multiple uncalibrated pinhole cameras. We find 291 minimal problems, 73 of which have unique solutions…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Kim Kiehn , Albin Ahlbäck , Kathlén Kohn

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 paper proposes a novel algorithm of discovering the structure of a kaleidoscopic imaging system that consists of multiple planar mirrors and a camera. The kaleidoscopic imaging system can be recognized as the virtual multi-camera…

Computer Vision and Pattern Recognition · Computer Science 2021-03-30 Kosuke Takahashi , Shohei Nobuhara

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