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Transfer Learning Based on A+ for Image Super-Resolution
[chapter]
2016
Lecture Notes in Computer Science
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Therefore, in this paper, a new algorithm Transfer Learning based on A+ (TLA) is proposed for image super-resolution task. ...
Example learning-based super-resolution (SR) methods are effective to generate a high-resolution (HR) image from a single low-resolution (LR) input. ...
Therefore, the transfer learning based on face images is beneficial to the performance of super-resolution task. ...
doi:10.1007/978-3-319-47650-6_26
fatcat:pnmziyjymvan5dm7dabisvdasm
Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks
[article]
2019
arXiv
pre-print
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Single-image super-resolution aims to generate a high-resolution version of a low-resolution image, which serves as an essential component in many computer vision applications. ...
This paper investigates the robustness of deep learning-based super-resolution methods against adversarial attacks, which can significantly deteriorate the super-resolved images without noticeable distortion ...
Figure 4 Figure 5 .Figure 6 . 456 summarizes the transferability for the deep learning-based super-resolution models on the BSD100 dataset, where α = 8/255. ...
arXiv:1904.06097v2
fatcat:672d2r2mmzdvtf55iynepz7yde
Small Object Detection from Remote Sensing Images with the Help of Object-Focused Super-Resolution Using Wasserstein GANs
2020
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
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Results showed that object-focused super-resolution improves the detection performance and facilitates the transfer learning from one data set to another. ...
The learning of our super-resolution network is performed using deep residual blocks integrated in a Wasserstein Generative adversarial network. ...
TRANSFER LEARNING In this section, we show that object-focused super-resolution could be useful within a transfer learning context. ...
doi:10.1109/igarss39084.2020.9323236
fatcat:b456ubp7hffk5mcw2oseux5beq
Meta-Transfer Learning for Zero-Shot Super-Resolution
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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In this paper, we present Meta-Transfer Learning for Zero-Shot Super-Resolution (MZSR), which leverages ZSSR. ...
Precisely, it is based on finding a generic initial parameter that is suitable for internal learning. ...
Then, meta-transfer learning learns a good representation θ M for super-resolution tasks with diverse blur kernel scenarios. The figure shows N tasks for simplicity. ...
doi:10.1109/cvpr42600.2020.00357
dblp:conf/cvpr/SohCC20
fatcat:xqqzijd545gxxg6rcty5ttchpa
Towards Domain Adaptive Vehicle Detection in Satellite Image by Supervised Super-Resolution Transfer
2016
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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learning to the high-resolution aerial image domain,where rich supervision exists and robust detectors can be trained.To this end, we first propose a super-resolution algorithm using coupled dictionary ...
of satellite images, as well as the limited training data.In this paper, a robust domain-adaptive vehicle detection framework is proposed to bypass both problems.Our innovation is to transfer the detector ...
(Kim and Kwon 2010) presented a spare regression based algorithm that adopts ridge regression for super-resolution of a single-frame image. ...
doi:10.1609/aaai.v30i1.10166
fatcat:siggikpu2rh2zo3cl7dngex56a
Generative Adversarial Networks for Image Super-Resolution: A Survey
[article]
2022
arXiv
pre-print
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Then, we analyze motivations, implementations and differences of GANs based optimization methods and discriminative learning for image super-resolution in terms of supervised, semi-supervised and unsupervised ...
Single image super-resolution (SISR) has played an important role in the field of image processing. ...
machine learning methods on image super-resolution [21] . ...
arXiv:2204.13620v1
fatcat:hlwdqith65cxrbqrnbphjz6u4u
Meta-Transfer Learning for Zero-Shot Super-Resolution
[article]
2020
arXiv
pre-print
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In this paper, we present Meta-Transfer Learning for Zero-Shot Super-Resolution (MZSR), which leverages ZSSR. ...
Precisely, it is based on finding a generic initial parameter that is suitable for internal learning. ...
Then, meta-transfer learning learns a good representation θ M for super-resolution tasks with diverse blur kernel scenarios. The figure shows N tasks for simplicity. ...
arXiv:2002.12213v1
fatcat:23yd4dwgtjcxnnkgmquav2bd4i
Adversarial Images Against Super-Resolution Convolutional Neural Networks for Free
2022
Proceedings on Privacy Enhancing Technologies
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Neural Networks (CNNs)-based image classifiers. ...
Super-Resolution Convolutional Neural Networks (SRCNNs) with their ability to generate highresolution images from low-resolution counterparts, exacerbate the privacy concerns emerging from automated Convolutional ...
Acknowledgements This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. ...
doi:10.56553/popets-2022-0065
fatcat:aew2plqqdvc4hlfgj37yc4vlsm
A Generative Adversarial Network for AI-Aided Chair Design
2019
2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)
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2020 pre-print arXiv:2001.11715v1 fatcat:4baloje6uncmnhhzng6evtgu4u
It consists of an image synthesis module, which learns the underlying distribution of training dataset, a super-resolution module, which improve quality of generated image and human involvements. ...
Finally, we manually pick one of the generated candidates to create a real life chair for illustration. ...
Image to Image Translation Image to Image translation methods have been successfully applied for style transfer and image super-resolution, which can be used as a powerful tool for auxiliary design.For ...
doi:10.1109/mipr.2019.00098
dblp:conf/mipr/LiuGW19
fatcat:wc5ijncuynhhxgt3an5n2e5vs4
Reference based Face Super-resolution
2019
IEEE Access
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We create a benchmark dataset on reference based face super-resolution (RefSR-Face) for general research use, which contains reference images paired with low-resolution images of various pose, emotions ...
We propose a novel Conditional Variational AutoEncoder model for this Reference based Face Super-Resolution (RefSR-VAE). ...
The neural style transfer is built based on a feed-forward network to transfer the style of the reference image to the input LR image to aid the super-resolution process. ...
doi:10.1109/access.2019.2934078
fatcat:qw6mh56ysvfpjbvno4hxn7sgwq
Image Super-resolution Using Mid-level Representations
2016
DEStech Transactions on Engineering and Technology Research
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An end-to-end six layers convolutional neural network(CNNs) structure is proposed to realize single image super-resolution reconstruction. ...
The input of the network is low-resolution (LR) image, and the output is the superresolution (SR) image. Promising experimental results are obtained with higher precision. ...
Sparse coding (SC) is a representative learning-based method for single image super-resolution reconstruction [4] . ...
doi:10.12783/dtetr/iect2016/3750
fatcat:7aqy4lax5bgj7i5v5b3frv6zsi
Fast Image Super-Resolution Based on In-Place Example Regression
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition
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We propose a fast regression model for practical single image super-resolution based on in-place examples, by leveraging two fundamental super-resolution approacheslearning from an external database and ...
Based on the in-place examples, a first-order approximation of the nonlinear mapping function from low-to high-resolution image patches is learned. ...
We propose a new fast super-resolution algorithm based on regression on in-place examples, which, for the first time, leverages the two fundamental super-resolution approaches of learning from externalexamples ...
doi:10.1109/cvpr.2013.141
dblp:conf/cvpr/YangLC13
fatcat:z4cbctbvmvhrtldah2i6rstvq4
A New Makeup Transfer with Super-resolution
2019
Australian Journal of Intelligent Information Processing Systems
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With the wide use of beauty camera, the makeup transfer for old photo has a certain application value. ...
In this paper, we propose a new makeup transfer model considering a specific scene that is blurry target image. ...
(a) A blurry target image; (b) Example image for makeup transfer.
Fig. 6 : 6 Fig. 6: The improvement of makeup transfer by super-resolution method. ...
dblp:journals/ajiips/RenSWCQ19
fatcat:rrgaioa2bjhkzm373vu37hzptu
A Comparable Study of CNN-Based Single Image Super-Resolution for Space-Based Imaging Sensors
2019
Sensors
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In this paper, we comparably study four recent popular models for single image super-resolution based on convolutional neural networks (CNNs) with the purpose of space applications. ...
We specially fine-tune the super-resolution models designed for natural images using simulated images of space objects, and test the performance of different CNN-based models in different conditions that ...
(Very Deep Super-resolution Convolutional Networks), and DRCN [43] (Deeply-Recursive Convolutional Networks) for single image super-resolution based on CNNs. ...
doi:10.3390/s19143234
fatcat:7kypbe2zmreqxdfduceodzggda
Anchored neighborhood deep network for single-image super-resolution
2018
EURASIP Journal on Image and Video Processing
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In this paper, we establish the relationship between the traditional sparse-representation-based single-image super-resolution methods and the deep-learning-based ones and use transfer learning to make ...
Therefore, how to make full use of image prior is one of the unsolved problems for deep-network-based single image super-resolution methods. ...
Acknowledgements We would like to acknowledge all our team members, especially Min Gao and Xinwei Gao, for their constructive suggestions on deep-learning-based image restoration and image compression. ...
doi:10.1186/s13640-018-0269-7
fatcat:spvm2uk5mjbetiurebb54gp7fy
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