[HTML][HTML] Deep learning in optical metrology: a review
With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
On the synergies between machine learning and binocular stereo for depth estimation from images: a survey
Stereo matching is one of the longest-standing problems in computer vision with close to 40
years of studies and research. Throughout the years the paradigm has shifted from local …
years of studies and research. Throughout the years the paradigm has shifted from local …
A survey on deep learning techniques for stereo-based depth estimation
Estimating depth from RGB images is a long-standing ill-posed problem, which has been
explored for decades by the computer vision, graphics, and machine learning communities …
explored for decades by the computer vision, graphics, and machine learning communities …
On the uncertainty of self-supervised monocular depth estimation
Self-supervised paradigms for monocular depth estimation are very appealing since they do
not require ground truth annotations at all. Despite the astonishing results yielded by such …
not require ground truth annotations at all. Despite the astonishing results yielded by such …
Vis-mvsnet: Visibility-aware multi-view stereo network
Learning-based multi-view stereo (MVS) methods have demonstrated promising results.
However, very few existing networks explicitly take the pixel-wise visibility into consideration …
However, very few existing networks explicitly take the pixel-wise visibility into consideration …
Real-time self-adaptive deep stereo
Deep convolutional neural networks trained end-to-end are the state-of-the-art methods to
regress dense disparity maps from stereo pairs. These models, however, suffer from a …
regress dense disparity maps from stereo pairs. These models, however, suffer from a …
Itermvs: Iterative probability estimation for efficient multi-view stereo
We present IterMVS, a new data-driven method for high-resolution multi-view stereo. We
propose a novel GRU-based estimator that encodes pixel-wise probability distributions of …
propose a novel GRU-based estimator that encodes pixel-wise probability distributions of …
Visibility-aware multi-view stereo network
Learning-based multi-view stereo (MVS) methods have demonstrated promising results.
However, very few existing networks explicitly take the pixel-wise visibility into consideration …
However, very few existing networks explicitly take the pixel-wise visibility into consideration …
Learning monocular depth estimation infusing traditional stereo knowledge
Depth estimation from a single image represents a fascinating, yet challenging problem with
countless applications. Recent works proved that this task could be learned without direct …
countless applications. Recent works proved that this task could be learned without direct …
Harnessing GPU tensor cores for fast FP16 arithmetic to speed up mixed-precision iterative refinement solvers
A Haidar, S Tomov, J Dongarra… - … Conference for High …, 2018 - ieeexplore.ieee.org
Low-precision floating-point arithmetic is a powerful tool for accelerating scientific computing
applications, especially those in artificial intelligence. Here, we present an investigation …
applications, especially those in artificial intelligence. Here, we present an investigation …