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Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution
[article]
2022
arXiv
pre-print
Preserved Fulltext
Efficient and effective real-world image super-resolution (Real-ISR) is a challenging task due to the unknown complex degradation of real-world images and the limited computation resources in practical ...
In this paper, we propose an efficient and effective degradation-adaptive super-resolution (DASR) network, whose parameters are adaptively specified by estimating the degradation of each input image. ...
Conclusion In this paper, we proposed an efficient degradation-adaptive network, namely DASR, for the real-world image super-resolution (Real-ISR) task. ...
arXiv:2203.14216v1
fatcat:ljrevrmj75d5ljqexd5hs2svvq
Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression
2021
IEEE Journal on Selected Topics in Signal Processing
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Also In "Multi-scale image super-resolution via a single extendable deep network" Zhang et al. propose a solution (MSWSR) addressing efficiency and arbitrary upscaling factors. ...
data drops sharply on real-world images/video, where the quantity and quality of training data is limited, and v) exploiting temporal correlations for efficient and effective video restoration and compression ...
doi:10.1109/jstsp.2021.3053364
fatcat:hjo5pvw6lvgpfga2wfq4vpaq3q
A Review on Self Learning based Methods for Real World Single Image Super Resolution
[chapter]
2021
New Frontiers in Communication and Intelligent Systems
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One of the active research issues in image processing is super resolution, which is used to boost picture resolution. ...
The super resolution of a single image is obtained by rebuilding high-resolution (HR) pictures from low-resolution (LR) damaged pho tos (RSISR). ...
As there are two major limitations of real-world images suffers from degradation problem therefore it is necessary to adapt RSISR models with ever changing real-world images. ...
doi:10.52458/978-81-95502-00-4-1
fatcat:wxz4mp33wzfvhafjx6plw5rnky
Toward Real-world Image Super-resolution via Hardware-based Adaptive Degradation Models
[article]
2021
arXiv
pre-print
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Most single image super-resolution (SR) methods are developed on synthetic low-resolution (LR) and high-resolution (HR) image pairs, which are simulated by a predetermined degradation operation, e.g., ...
We design an adaptive blurring layer (ABL) in the supervised learning framework to estimate the target LR images. The hyperparameters of the ABL can be adjusted for different imaging hardware. ...
Experimental Setups
Dataset SupER dataset is a newly proposed high-quality paired HR and LR image dataset for real-world image super-resolution tasks. ...
arXiv:2110.10755v1
fatcat:m42bndrminhdpcsktrjv7qt3pa
Real-Time Super-Resolution for Real-World Images on Mobile Devices
[article]
2022
arXiv
pre-print
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Extensive experiments on traditional super-resolution datasets (Set5, Set14, BSD100, Urban100, Manga109, DIV2K) and real-world images with a variety of degradations demonstrate that our method outperforms ...
In this work, an approach for real-time ISR on mobile devices is presented, which is able to deal with a wide range of degradations in real-world scenarios. ...
The AIM 2019 Challenge on Real-World Image Super-Resolution [23] and the NTIRE 2020 Challenge on Real-World Image Super-Resolution [22] aim to stimulate research in the direction of real-world ISR, ...
arXiv:2206.01777v1
fatcat:itcigackyrc2tpemwnsadqfimy
Real-World Single Image Super-Resolution: A Brief Review
[article]
2021
arXiv
pre-print
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This article aims to make a comprehensive review on real-world single image super-resolution (RSISR). ...
Recent studies show that simulation results on synthetic data usually overestimate the capacity to super-resolve real-world images. ...
., realistic datasets for model training and testing, specific models for real-world image super-resolution and reconstruction performance evaluation. ...
arXiv:2103.02368v1
fatcat:fesf6ercffdxdg7jx3mda6nkri
Learning Multiple Probabilistic Degradation Generators for Unsupervised Real World Image Super Resolution
[article]
2022
arXiv
pre-print
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Unsupervised real world super resolution (USR) aims at restoring high-resolution (HR) images given low-resolution (LR) inputs when paired data is unavailable. ...
Instead, we propose the probabilistic degradation generator. Our degradation generator is a deep hierarchical latent variable model and more suitable for modeling the complex distribution. ...
GAN-based Unsupervised Real-World Super Resolution Although SR models achieved remarkable results on bicubicdownsampled data, they perform poorly in the real world. ...
arXiv:2201.10747v1
fatcat:sl4wa5quyjelboxr7nr6y2tfp4
Closed-Loop Matters: Dual Regression Networks for Single Image Super-Resolution
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Deep neural networks have exhibited promising performance in image super-resolution (SR) by learning a nonlinear mapping function from low-resolution (LR) images to high-resolution (HR) images. ...
Second, the paired LR-HR data may be unavailable in real-world applications and the underlying degradation method is often unknown. ...
and unpaired real-world data demonstrate the effectiveness of the proposed dual regression scheme in image super-resolution. ...
doi:10.1109/cvpr42600.2020.00545
dblp:conf/cvpr/GuoCWCCDXT20
fatcat:7pavob63kndtxetrggnh6xr7um
Learning Omni-frequency Region-adaptive Representations for Real Image Super-Resolution
[article]
2021
arXiv
pre-print
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Traditional single image super-resolution (SISR) methods that focus on solving single and uniform degradation (i.e., bicubic down-sampling), typically suffer from poor performance when applied into real-world ...
The key to solving this more challenging real image super-resolution (RealSR) problem lies in learning feature representations that are both informative and content-aware. ...
With the development of deep learning, a series of studies (Pan et al. 2020; Dong et al. 2015; Lim et al. 2017; Dong, Loy, and Tang 2016) have achieved great progress on traditional super-resolution ...
arXiv:2012.06131v2
fatcat:m7j6bu75lvek3ppj2gqrpjuu3u
Deep Degradation Prior for Real-World Super-Resolution
2021
British Machine Vision Conference
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Real-world Super-Resolution (SR) is a very challenging task to reconstruct a higher resolution image from a real-world image which generally has unexpected artifacts and distortions. ...
The methods estimate the noises and the blur kernels from real-world images to generate a new training set. However, these methods use the degradation only for dataset construction. ...
Real-World Super-Resolution Real-world SR is a task that makes a blurry and noisy image taken with a real camera or smartphone into a clean HR image. Therefore, there is no LR-HR paired dataset. ...
dblp:conf/bmvc/KoLHHK21
fatcat:xv5kkflruzgy7amuslyor4x4xm
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
[article]
2020
arXiv
pre-print
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The goal is to attract more attention to realistic image degradation for the SR task, which is much more complicated and challenging, and contributes to real-world image super-resolution applications. ...
They gauge the state-of-the-art approaches for real image SR in terms of PSNR and SSIM. ...
ALONG The ALONG team proposed Dual Path Network with high frequency guided for real-world image Super-Resolution. ...
arXiv:2009.12072v1
fatcat:7cwsjfhqa5cf7avfvdabpmxrda
Learning a Degradation-Adaptive Network for Light Field Image Super-Resolution
[article]
2022
arXiv
pre-print
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Recent years have witnessed the great advances of deep neural networks (DNNs) in light field (LF) image super-resolution (SR). ...
Extensive experiments on both synthetically degraded and real-world LFs demonstrate the effectiveness of our method. ...
degradation models to train deep networks for real-world SR. ...
arXiv:2206.06214v1
fatcat:dlulqxvtxzhy3lhlnjpvazrq34
A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution
[article]
2021
arXiv
pre-print
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To handle the multiple degradation, i.e. refers to multi-domain image super-resolution, we propose a deep Super-Resolution Residual StarGAN (SR2*GAN), a novel and scalable approach that super-resolves ...
However, in real-world settings, the LR degradation process is unknown which can be bicubic LR, bilinear LR, nearest-neighbor LR, or real LR. ...
In the real-world settings, the input LR image contains more complex degradation. ...
arXiv:2107.03145v1
fatcat:r6ql5ofkijevpcg2jgksjpzw5i
NTIRE 2019 Challenge on Real Image Super-Resolution: Methods and Results
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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They gauge the state-of-the-art in real-world single image super-resolution. ...
The challenge had 1 track, which was aimed at the real-world single image super-resolution problem with an unknown scaling factor. ...
., ETH Zurich, and The Hong Kong Polytechnic University.
A. Teams and affiliations NTIRE2019 team ...
doi:10.1109/cvprw.2019.00274
dblp:conf/cvpr/CaiGTZa19
fatcat:tynb7gtpdvbfnbmugtelgcxude
Exploiting Style and Attention in Real-World Super-Resolution
[article]
2020
arXiv
pre-print
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2019 pre-print arXiv:1912.10227v1 fatcat:lrxdtrvx55gozlwn5su3mjpheq
Real-world image super-resolution (SR) is a challenging image translation problem. ...
To get real-world-like low-quality images paired with the HR images, we design the styleVAE to transfer the complex nuisance factors in real-world LR images to the generated LR images. ...
In addition to styleVAE, we build a SR network for realworld super-resolution. ...
arXiv:1912.10227v2
fatcat:e5c5dbbmtjdfjdtdabsw4rrybm
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