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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

We propose a novel method to accurately reconstruct a set of images representing a single scene from few linear multi-view measurements. Each observed image is modeled as the sum of a background image and a foreground one. The background…

Computer Vision and Pattern Recognition · Computer Science 2013-09-19 Gilles Puy , Pierre Vandergheynst

Statistical shape modeling (SSM) is an essential tool for analyzing variations in anatomical morphology. In a typical SSM pipeline, 3D anatomical images, gone through segmentation and rigid registration, are represented using…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Hong Xu , Shireen Y. Elhabian

Existing works on motion deblurring either ignore the effects of depth-dependent blur or work with the assumption of a multi-layered scene wherein each layer is modeled in the form of fronto-parallel plane. In this work, we consider the…

Computer Vision and Pattern Recognition · Computer Science 2022-02-08 Kuldeep Purohit , Subeesh Vasu , M. Purnachandra Rao , A. N. Rajagopalan

Reconstructing complex structures from planar cross-sections is a challenging problem, with wide-reaching applications in medical imaging, manufacturing, and topography. Out-of-the-box point cloud reconstruction methods can often fail due…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Thomas Walker , Salvatore Esposito , Daniel Rebain , Amir Vaxman , Arno Onken , Changjian Li , Oisin Mac Aodha

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

We introduce a novel framework that integrates Neural Radiance Fields (NeRF) with Material Point Method (MPM) simulation to infer granular material properties from visual observations. Our approach begins by generating synthetic…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Cheng-Hsi Hsiao , Krishna Kumar

Predicting accurate normal maps of objects from two-dimensional images in regions of complex structure and spatial material variations is challenging using photometric stereo methods due to the influence of surface reflection properties…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Kai Luo , Yakun Ju , Lin Qi , Kaixuan Wang , Junyu Dong

We present Light3R-SfM, a feed-forward, end-to-end learnable framework for efficient large-scale Structure-from-Motion (SfM) from unconstrained image collections. Unlike existing SfM solutions that rely on costly matching and global…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Sven Elflein , Qunjie Zhou , Sérgio Agostinho , Laura Leal-Taixé

Structure from Motion or the sparse 3D reconstruction out of individual photos is a long studied topic in computer vision. Yet none of the existing reconstruction pipelines fully addresses a progressive scenario where images are only…

Computer Vision and Pattern Recognition · Computer Science 2018-07-12 Alex Locher , Michal Havlena , Luc Van Gool

Image based modeling and laser scanning are two commonly used approaches in large-scale architectural scene reconstruction nowadays. In order to generate a complete scene reconstruction, an effective way is to completely cover the scene…

Computer Vision and Pattern Recognition · Computer Science 2019-09-19 Xiang Gao , Shuhan Shen , Lingjie Zhu , Tianxin Shi , Zhiheng Wang , Zhanyi Hu

Single-image 3D reconstruction with large reconstruction models (LRMs) has advanced rapidly, yet reconstructions often exhibit geometric inconsistencies and misaligned details that limit fidelity. We introduce GeoFusionLRM, a geometry-aware…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Ahmet Burak Yildirim , Tuna Saygin , Duygu Ceylan , Aysegul Dundar

Geometry estimation from perspective images has greatly advanced, maturing to the point where off-the-shelf foundation models are able to reconstruct 3D scene structure not only from multi-view imagery, but even from a single view. A…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Vukasin Bozic , Isidora Slavkovic , Dominik Narnhofer , Nando Metzger , Denis Rozumny , Konrad Schindler , Nikolai Kalischek

Structure and continuous motion estimation from point correspondences is a fundamental problem in computer vision that has been powered by well-known algorithms such as the familiar 5-point or 8-point algorithm. However, despite their…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Hang Su , Yunlong Feng , Daniel Gehrig , Panfeng Jiang , Ling Gao , Xavier Lagorce , Laurent Kneip

Super-resolution reconstruction (SRR) is a process aimed at enhancing spatial resolution of images, either from a single observation, based on the learned relation between low and high resolution, or from multiple images presenting the same…

Computer Vision and Pattern Recognition · Computer Science 2020-06-24 Michal Kawulok , Pawel Benecki , Szymon Piechaczek , Krzysztof Hrynczenko , Daniel Kostrzewa , Jakub Nalepa

The recovery of 3D shape and pose from 2D landmarks stemming from a large ensemble of images can be viewed as a non-rigid structure from motion (NRSfM) problem. Classical NRSfM approaches, however, are problematic as they rely on heuristic…

Computer Vision and Pattern Recognition · Computer Science 2021-04-01 Chaoyang Wang , Chen-Hsuan Lin , Simon Lucey

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

We introduce the distributed camera model, a novel model for Structure-from-Motion (SfM). This model describes image observations in terms of light rays with ray origins and directions rather than pixels. As such, the proposed model is…

Computer Vision and Pattern Recognition · Computer Science 2016-12-02 Chris Sweeney , Victor Fragoso , Tobias Hollerer , Matthew Turk

Even though Non-rigid Structure-from-Motion (NRSfM) has been extensively studied and great progress has been made, there are still key challenges that hinder their broad real-world applications: 1) the inherent motion/rotation ambiguity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Jiawei Shi , Hui Deng , Yuchao Dai

Structure from motion (SfM) enables us to reconstruct a scene via casual capture from cameras at different viewpoints, and novel view synthesis (NVS) allows us to render a captured scene from a new viewpoint. Both are hard with casual…