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Related papers: End-to-End Multi-View Structure-from-Motion with H…

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In addition to color and textural information, geometry provides important cues for 3D scene reconstruction. However, current reconstruction methods only include geometry at the feature level thus not fully exploiting the geometric…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Ruihong Yin , Sezer Karaoglu , Theo Gevers

Non-Rigid structure from motion (NRSfM), is a long standing and central problem in computer vision and its solution is necessary for obtaining 3D information from multiple images when the scene is dynamic. A main issue regarding the further…

Computer Vision and Pattern Recognition · Computer Science 2020-11-12 Sebastian Hoppe Nesgaard Jensen , Mads Emil Brix Doest , Henrik Aanaes , Alessio Del Bue

Diffusion models have recently emerged as a powerful technique in image generation, especially for image super-resolution tasks. While 2D diffusion models significantly enhance the resolution of individual images, existing diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Bohao Chen , Yanchao Zhang , Yanan Lv , Hua Han , Xi Chen

While Structure from Motion (SfM) achieves great success in 3D reconstruction, it still meets challenges on large scale scenes. In this work, large scale SfM is deemed as a graph problem, and we tackle it in a divide-and-conquer manner.…

Computer Vision and Pattern Recognition · Computer Science 2020-06-09 Yu Chen , Shuhan Shen , Yisong Chen , Guoping Wang

Recovering the 3D shape of an object from single or multiple images with deep neural networks has been attracting increasing attention in the past few years. Mainstream works (e.g. 3D-R2N2) use recurrent neural networks (RNNs) to…

Computer Vision and Pattern Recognition · Computer Science 2020-10-06 Haozhe Xie , Hongxun Yao , Shengping Zhang , Shangchen Zhou , Wenxiu Sun

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

Central to the application of many multi-view geometry algorithms is the extraction of matching points between multiple viewpoints, enabling classical tasks such as camera pose estimation and 3D reconstruction. Many approaches that…

Computer Vision and Pattern Recognition · Computer Science 2021-10-15 Alexander Mai , Allen Yang , Dominique E. Meyer

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

Existing methods for reconstructing objects and humans from a monocular image suffer from severe mesh collisions and performance limitations for interacting occluding objects. This paper introduces a method to obtain a globally consistent…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Sarthak Batra , Partha P. Chakrabarti , Simon Hadfield , Armin Mustafa

Reconstructing 3D objects from a single image is an intriguing but challenging problem. One promising solution is to utilize multi-view (MV) 3D reconstruction to fuse generated MV images into consistent 3D objects. However, the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Yizheng Chen , Rengan Xie , Qi Ye , Sen Yang , Zixuan Xie , Tianxiao Chen , Rong Li , Yuchi Huo

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

Non-rigid structure-from-motion (NRSfM), a promising technique for addressing the mapping challenges in monocular visual deformable simultaneous localization and mapping (SLAM), has attracted growing attention. We introduce a novel method,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Yongbo Chen , Yanhao Zhang , Shaifali Parashar , Liang Zhao , Shoudong Huang

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

We address the task of estimating camera parameters from a set of images depicting a scene. Popular feature-based structure-from-motion (SfM) tools solve this task by incremental reconstruction: they repeat triangulation of sparse 3D points…

Computer Vision and Pattern Recognition · Computer Science 2024-07-29 Eric Brachmann , Jamie Wynn , Shuai Chen , Tommaso Cavallari , Áron Monszpart , Daniyar Turmukhambetov , Victor Adrian Prisacariu

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang

We present MatDecompSDF, a novel framework for recovering high-fidelity 3D shapes and decomposing their physically-based material properties from multi-view images. The core challenge of inverse rendering lies in the ill-posed…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Chengyu Wang , Isabella Bennett , Henry Scott , Liang Zhang , Mei Chen , Hao Li , Rui Zhao

A key question in the problem of 3D reconstruction is how to train a machine or a robot to model 3D objects. Many tasks like navigation in real-time systems such as autonomous vehicles directly depend on this problem. These systems usually…

Computer Vision and Pattern Recognition · Computer Science 2022-09-22 AmirHossein Zamani , Amir G. Aghdam , Kamran Ghaffari T

The availability of affordable 3D full body reconstruction systems has given rise to free-viewpoint video (FVV) of human shapes. Most existing solutions produce temporally uncorrelated point clouds or meshes with unknown point/vertex…

Computer Vision and Pattern Recognition · Computer Science 2018-10-15 Zhong Li , Minye Wu , Wangyiteng Zhou , Jingyi Yu

Volumetric models have become a popular representation for 3D scenes in recent years. One of the breakthroughs leading to their popularity was KinectFusion, where the focus is on 3D reconstruction using RGB-D sensors. However, monocular…

Computer Vision and Pattern Recognition · Computer Science 2014-10-27 Victor Adrian Prisacariu , Olaf Kähler , Ming Ming Cheng , Carl Yuheng Ren , Julien Valentin , Philip H. S. Torr , Ian D. Reid , David W. Murray

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