Multi-view stereo: A tutorial
This tutorial presents a hands-on view of the field of multi-view stereo with a focus on
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …
Cascade residual learning: A two-stage convolutional neural network for stereo matching
Leveraging on the recent developments in convolutional neural networks (CNNs), matching
dense correspondence from a stereo pair has been cast as a learning problem, with …
dense correspondence from a stereo pair has been cast as a learning problem, with …
A survey on conventional and learning‐based methods for multi‐view stereo
Abstract 3D reconstruction of scenes using multiple images, relying on robust
correspondence search and depth estimation, has been thoroughly studied for the two‐view …
correspondence search and depth estimation, has been thoroughly studied for the two‐view …
[كتاب][B] Computer vision: algorithms and applications
R Szeliski - 2022 - books.google.com
Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …
despite all of the recent advances in computer vision research, the dream of having a …
A taxonomy and evaluation of dense two-frame stereo correspondence algorithms
Stereo matching is one of the most active research areas in computer vision. While a large
number of algorithms for stereo correspondence have been developed, relatively little work …
number of algorithms for stereo correspondence have been developed, relatively little work …
Fast approximate energy minimization via graph cuts
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A
common constraint is that the labels should vary smoothly almost everywhere while …
common constraint is that the labels should vary smoothly almost everywhere while …
Daisy: An efficient dense descriptor applied to wide-baseline stereo
In this paper, we introduce a local image descriptor, DAISY, which is very efficient to
compute densely. We also present an EM-based algorithm to compute dense depth and …
compute densely. We also present an EM-based algorithm to compute dense depth and …
Efficient belief propagation for early vision
Markov random field models provide a robust and unified framework for early vision
problems such as stereo and image restoration. Inference algorithms based on graph cuts …
problems such as stereo and image restoration. Inference algorithms based on graph cuts …
Evaluation of cost functions for stereo matching
Stereo correspondence methods rely on matching costs for computing the similarity of image
locations. In this paper we evaluate the insensitivity of different matching costs with respect …
locations. In this paper we evaluate the insensitivity of different matching costs with respect …
Stereo matching using belief propagation
In this paper, we formulate the stereo matching problem as a Markov network and solve it
using Bayesian belief propagation. The stereo Markov network consists of three coupled …
using Bayesian belief propagation. The stereo Markov network consists of three coupled …