Super-resolution: a comprehensive survey
K Nasrollahi, TB Moeslund - Machine vision and applications, 2014 - Springer
Super-resolution, the process of obtaining one or more high-resolution images from one or
more low-resolution observations, has been a very attractive research topic over the last two …
more low-resolution observations, has been a very attractive research topic over the last two …
Noise robust face hallucination via locality-constrained representation
Recently, position-patch based approaches have been proposed to replace the probabilistic
graph-based or manifold learning-based models for face hallucination. In order to obtain the …
graph-based or manifold learning-based models for face hallucination. In order to obtain the …
Face super-resolution via multilayer locality-constrained iterative neighbor embedding and intermediate dictionary learning
Based on the assumption that low-resolution (LR) and high-resolution (HR) manifolds are
locally isometric, the neighbor embedding super-resolution algorithms try to preserve the …
locally isometric, the neighbor embedding super-resolution algorithms try to preserve the …
Facial image hallucination through coupled-layer neighbor embedding
As the facial image captured by a low-cost camera is typically very low resolution (LR),
blurring, and noisy, traditional neighbor-embedding-based facial image hallucination …
blurring, and noisy, traditional neighbor-embedding-based facial image hallucination …
Learning face image super-resolution through facial semantic attribute transformation and self-attentive structure enhancement
Face super-resolution is a domain-specific super-resolution (SR) problem of generating high-
resolution (HR) face images from low-resolution (LR) inputs. Even though existing face SR …
resolution (HR) face images from low-resolution (LR) inputs. Even though existing face SR …
Fast, accurate and detailed NoC simulations
PT Wolkotte, PKF Holzenspies… - … Symposium on Networks …, 2007 - ieeexplore.ieee.org
Network-on-chip (NoC) architectures have a wide variety of parameters that can be adapted
to the designer's requirements. Fast exploration of this parameter space is only possible at a …
to the designer's requirements. Fast exploration of this parameter space is only possible at a …
Face hallucination using linear models of coupled sparse support
RA Farrugia, C Guillemot - IEEE Transactions on Image …, 2017 - ieeexplore.ieee.org
Most face super-resolution methods assume that low-and high-resolution manifolds have
similar local geometrical structure; hence, learn local models on the low-resolution manifold …
similar local geometrical structure; hence, learn local models on the low-resolution manifold …
Parsing map guided multi-scale attention network for face hallucination
Face hallucination that aims to transform a low-resolution (LR) face image to a high-
resolution (HR) one is an active domain-specific image super-resolution problem. The …
resolution (HR) one is an active domain-specific image super-resolution problem. The …
Locality-constraint iterative neighbor embedding for face hallucination
Based on the assumption that low-resolution (LR) and high-resolution (HR) patch manifolds
are locally isometric, the neighbor embedding based super-resolution algorithms try to …
are locally isometric, the neighbor embedding based super-resolution algorithms try to …
Global consistency, local sparsity and pixel correlation: A unified framework for face hallucination
In this paper, a novel two-phase framework is presented to deal with the face hallucination
problem. In the first phase, an initial high-resolution (HR) face image is produced in patch …
problem. In the first phase, an initial high-resolution (HR) face image is produced in patch …