EK Stathopoulou, M Welponer… - The International Archives …, 2019 - cris.fbk.eu
State-of-the-art automated image orientation (Structure from Motion) and dense image matching (Multiple View Stereo) methods commonly used to produce 3D information from …
We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo. With high computation speed and low memory …
This paper introduces the Meshroom software and its underlying 3D computer vision framework AliceVision. This solution provides a photogrammetry pipeline to reconstruct 3D …
Y Yao, Z Luo, S Li, T Fang… - Proceedings of the …, 2018 - openaccess.thecvf.com
We present an end-to-end deep learning architecture for depth map inference from multi- view images. In the network, we first extract deep visual image features, and then build the …
With the pervasive use of Building Information Modelling (BIM), lean principles, digital technologies, and offsite construction, the industry is at the cusp of this transformation. The …
PH Huang, K Matzen, J Kopf… - Proceedings of the …, 2018 - openaccess.thecvf.com
We present DeepMVS, a deep convolutional neural network (ConvNet) for multi-view stereo reconstruction. Taking an arbitrary number of posed images as input, we first produce a set …
This paper describes how to obtain accurate 3D body models and texture of arbitrary people from a single, monocular video in which a person is moving. Based on a parametric body …
B Ummenhofer, H Zhou, J Uhrig… - Proceedings of the …, 2017 - openaccess.thecvf.com
In this paper we formulate structure from motion as a learning problem. We train a convolutional network end-to-end to compute depth and camera motion from successive …
K Luo, T Guan, L Ju, H Huang… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
Learning-based methods are demonstrating their strong competitiveness in estimating depth for multi-view stereo reconstruction in recent years. Among them the approaches that …