为方便查阅,倒序记录文献。
偶尔会加Inpainting,Denoising,Deblur,Artifacts removal,Dehazing,Demosaicing等方面内容。
资料源自卡内基大学文献库:https://arxiv.org/list/cs/recent
格式参考爱可可老师,简书链接:https://www.jianshu.com/u/ZQtGe6
20190730
Image Enhancement by Recurrently-trained Super-resolution Network
Saem Park, Nojun Kwak
http://arxiv.org/abs/1907.11341v1
20190726
Progressive Perception-Oriented Network for Single Image Super-Resolution
Zheng Hui, Jie Li, Xinbo Gao, Xiumei Wang
http://arxiv.org/abs/1907.10399v1
Blind Deblurring using Deep Learning: A Survey
Siddhant Sahu, Manoj Kumar Lenka, Pankaj Kumar Sa
http://arxiv.org/abs/1907.10128v1
Image Super-Resolution Using a Wavelet-based Generative Adversarial Network
Qi Zhang, Huafeng Wang, Sichen Yang
http://arxiv.org/abs/1907.10213v1
20190720
Diving Deeper into Underwater Image Enhancement: A Survey
Saeed Anwar, Chongyi Li
http://arxiv.org/abs/1907.07863v1
20190718
Boosting Resolution and Recovering Texture of micro-CT Images with Deep Learning
Ying Da Wang, Ryan T. Armstrong, Peyman Mostaghimi
http://arxiv.org/abs/1907.07131v1
20190717
Perceptually Motivated Method for Image Inpainting Comparison
Ivan Molodetskikh, Mikhail Erofeev, Dmitry Vatolin
http://arxiv.org/abs/1907.06296v1
DeepSUM: Deep neural network for Super-resolution of Unregistered Multitemporal images
Andrea Bordone Molini, Diego Valsesia, Giulia Fracastoro, Enrico Magli
http://arxiv.org/abs/1907.06490v1
20170716
Hybrid Residual Attention Network for Single Image Super Resolution
Abdul Muqeet, Md Tauhid Bin Iqbal, Sung-Ho Bae
http://arxiv.org/abs/1907.05514v1
Coupled-Projection Residual Network for MRI Super-Resolution
Chun-Mei Feng, Kai Wang, Shijian Lu, Yong Xu, Heng Kong, Ling Shao
http://arxiv.org/abs/1907.05598v1
Jointly Adversarial Network to Wavelength Compensation and Dehazing of Underwater Images
Xueyan Ding, Yafei Wang, Yang Yan, Zheng Liang, Zetian Mi, Xianping Fu
http://arxiv.org/abs/1907.05595v1
20190713
Enhanced generative adversarial network for 3D brain MRI super-resolution
Jiancong Wang, Yuhua Chen, Yifan Wu, Jianbo Shi, James Gee
http://arxiv.org/abs/1907.04835v1
20190712
Joint Learning of Multiple Image Restoration Tasks
Xing Liu, Masanori Suganuma, Takayuki Okatani
http://arxiv.org/abs/1907.04508v1
20190711
Gated Multiple Feedback Network for Image Super-Resolution
Qilei Li, Zhen Li, Lu Lu, Gwanggil Jeon, Kai Liu, Xiaomin Yang
http://arxiv.org/abs/1907.04253v1
Fully Convolutional Network for Removing DCT Artefacts From Images
Patryk Najgebauer, Rafal Scherer
http://arxiv.org/abs/1907.03798v1
20190710
FC$^2$N: Fully Channel-Concatenated Network for Single Image Super-Resolution
Xiaole Zhao, Ying Liao, Ye Li, Tao Zhang, Xueming Zou
http://arxiv.org/abs/1907.03221v1
MRI Super-Resolution with Ensemble Learning and Complementary Priors
Qing Lyu, Hongming Shan, Ge Wang
http://arxiv.org/abs/1907.03063v1
Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning
Majed El Helou, Sabine Susstrunk
http://arxiv.org/abs/1907.03029v1
An Experimental-based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
Yan Wang, Wei Song, Giancarlo Fortino, Lizhe Qi, Wenqiang Zhang, Antonio Liotta
http://arxiv.org/abs/1907.03246v1
Multi-level Wavelet Convolutional Neural Networks
Pengju Liu, Hongzhi Zhang, Wei Lian, Wangmeng Zuo
http://arxiv.org/abs/1907.03128v1
20190615
Unsupervised Image Noise Modeling with Self-Consistent GAN
Hanshu Yan, Vincent Tan, Wenhan Yang, Jiashi Feng
http://arxiv.org/abs/1906.05762v1
20190614
Suppressing Model Overfitting for Image Super-Resolution Networks
Ruicheng Feng, Jinjin Gu, Yu Qiao, Chao Dong
http://arxiv.org/abs/1906.04809v1
20190613
Hybrid Function Sparse Representation towards Image Super Resolution
Junyi Bian, Baojun Lin, Ke Zhang
http://arxiv.org/abs/1906.04363v1
FAMED-Net: A Fast and Accurate Multi-scale End-to-end Dehazing Network
Jing Zhang, Dacheng Tao
http://arxiv.org/abs/1906.04334v1
Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior
Yuanchao Bai, Huizhu Jia, Ming Jiang, Xianming Liu, Xiaodong Xie, Wen Gao
http://arxiv.org/abs/1906.04442v1
20190612
Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples
Dufan Wu, Kuang Gong, Kyungsang Kim, Quanzheng Li
http://arxiv.org/abs/1906.03639v1
20190606
3D Appearance Super-Resolution with Deep Learning
Yawei Li, Vagia Tsiminaki, Radu Timofte, Marc Pollefeys, Luc van Gool
http://arxiv.org/abs/1906.00925v2
Learning Deep Image Priors for Blind Image Denoising
Xianxu Hou, Hongming Luo, Jingxin Liu, Bolei Xu, Ke Sun, Yuanhao Gong, Bozhi Liu, Guoping Qiu
http://arxiv.org/abs/1906.01259v1
Natural Image Noise Dataset
Benoit Brummer, Christophe De Vleeschouwer
http://arxiv.org/abs/1906.00270v1
20190531
Coherent Semantic Attention for Image Inpainting
Hongyu Liu, Bin Jiang, Yi Xiao, Chao Yang
http://arxiv.org/abs/1905.12384v1
Image Denoising with Graph-Convolutional Neural Networks (ICIP2019)
Diego Valsesia, Giulia Fracastoro, Enrico Magli
http://arxiv.org/abs/1905.12281v1
20190530
Towards Real Scene Super-Resolution with Raw Images (CVPR2019)
Xiangyu Xu, Yongrui Ma, Wenxiu Sun
https://arxiv.org/abs/1905.12156
20190529
Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation
Hanyang Kong, Jian Zhao, Xiaoguang Tu, Junliang Xing, Shengmei Shen, Jiashi Feng
http://arxiv.org/abs/1905.10777v1
GAN2GAN: Generative Noise Learning for Blind Image Denoising with Single Noisy Images
Sungmin Cha, Taeeon Park, Taesup Moon
http://arxiv.org/abs/1905.10488v1
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling
Dong-Wook Kim, Jae Ryun Chung, Seung-Won Jung
http://arxiv.org/abs/1905.11172v1
20190524
PEPSI++: Fast and Lightweight Network for Image Inpainting
Yong-Goo Shin, Min-Cheol Sagong, Yoon-Jae Yeo, Seung-Wook Kim, Sung-Jea Ko
http://arxiv.org/abs/1905.09010v1
Segmentation-Aware Image Denoising without Knowing True Segmentation
Sicheng Wang, Bihan Wen, Junru Wu, Dacheng Tao, Zhangyang Wang
http://arxiv.org/abs/1905.08965v1
20190522
Less Memory, Faster Speed: Refining Self-Attention Module for Image Reconstruction
Zheng Wang, Jianwu Li, Ge Song, Tieling Li
http://arxiv.org/abs/1905.08008v1
20190518
FH-GAN: Face Hallucination and Recognition using Generative Adversarial Network
Bayram Bayramli, Usman Ali, Te Qi, Hongtao Lu
http://arxiv.org/abs/1905.06537v1
20190516
Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN)
Chris M. Ward, Josh Harguess, Brendan Crabb, Shibin Parameswaran
http://arxiv.org/abs/1905.05373v1
20190515
Ensemble Super-Resolution with A Reference Dataset
Junjun Jiang, Yi Yu, Zheng Wang, Suhua Tang, Ruimin Hu, Jiayi Ma
http://arxiv.org/abs/1905.04696v1
Joint demosaicing and denoising by overfitting of bursts of raw images
Thibaud Ehret, Axel Davy, Pablo Arias, Gabriele Facciolo
http://arxiv.org/abs/1905.05092v1
Medical image super-resolution method based on dense blended attention network
Kewen Liu, Yuan Ma, Hongxia Xiong, Zejun Yan, Zhijun Zhou, Panpan Fang, Chaoyang Liu
http://arxiv.org/abs/1905.05084v1
Zoom To Learn, Learn To Zoom
Xuaner Cecilia Zhang, Qifeng Chen, Ren Ng, Vladlen Koltun
http://arxiv.org/abs/1905.05169v1
20190510
Handheld Multi-Frame Super-Resolution (SIGGRAPH2019)
Bartlomiej Wronski, Ignacio Garcia-Dorado, Manfred Ernst, Damien Kelly, Michael Krainin, Chia-Kai Liang, Marc Levoy, Peyman Milanfar
https://arxiv.org/abs/1905.03277
Deep Flow-Guided Video Inpainting (CVPR2019)
Rui Xu, Xiaoxiao Li, Bolei Zhou, Chen Change Loy
http://arxiv.org/abs/1905.02884v1
Frame-Recurrent Video Inpainting by Robust Optical Flow Inference
Yifan Ding, Chuan Wang, Haibin Huang, Jiaming Liu, Jue Wang, Liqiang Wang
http://arxiv.org/abs/1905.02882v1
20190509
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks (CVPRW)
Xintao Wang, Kelvin C. K. Chan, Ke Yu, Chao Dong, Chen Change Loy
http://arxiv.org/abs/1905.02716v1
Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution
Chao Li, Dongliang He, Xiao Liu, Yukang Ding, Shilei Wen
http://arxiv.org/abs/1905.02462v1
Trinity of Pixel Enhancement: a Joint Solution for Demosaicking, Denoising and Super-Resolution
Guocheng Qian, Jinjin Gu, Jimmy S. Ren, Chao Dong, Furong Zhao, Juan Lin
http://arxiv.org/abs/1905.02538v1
20190508
Deep Video Inpainting (CVPR)
Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon
http://arxiv.org/abs/1905.01639v1
Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning (TPAMI)
Yukai Shi, Guanbin Li, Qingxing Cao, Keze Wang, Liang Lin
http://arxiv.org/abs/1905.01509v1
20190507
Generating Classification Weights with GNN Denoising Autoencoders for Few-Shot Learning (CVPR)
Spyros Gidaris, Nikos Komodakis
http://arxiv.org/abs/1905.01102v1
20190503
Multi-level Encoder-Decoder Architectures for Image Restoration
Indra Deep Mastan, Shanmuganathan Raman
http://arxiv.org/abs/1905.00322v1
20190501
An approach to image denoising using manifold approximation without clean images
Rohit Jena
http://arxiv.org/abs/1904.12323v1
Spatio-Temporal Filter Adaptive Network for Video Deblurring
Shangchen Zhou, Jiawei Zhang, Jinshan Pan, Haozhe Xie, Wangmeng Zuo, Jimmy Ren
http://arxiv.org/abs/1904.12257v1
Unsupervised and Unregistered Hyperspectral Image Super-Resolution with Mutual Dirichlet-Net
Ying Qu, Hairong Qi, Chiman Kwan
http://arxiv.org/abs/1904.12175v1
20190426
Multi-scale deep neural networks for real image super-resolution
Shangqi Gao, Xiahai Zhuang
http://arxiv.org/abs/1904.10698v1
Super-resolution based generative adversarial network using visual perceptual loss function
Xuan Zhu, Yue Cheng, Rongzhi Wang
http://arxiv.org/abs/1904.10654v1
ViDeNN: Deep Blind Video Denoising
Michele Claus, Jan van Gemert
http://arxiv.org/abs/1904.10898v1
20190425
Adaptive Transform Domain Image Super-resolution Via Orthogonally Regularized Deep Networks
Tiantong Guo, Hojjat S. Mousavi, Vishal Monga
http://arxiv.org/abs/1904.10082v1
Path-Restore: Learning Network Path Selection for Image Restoration
Ke Yu, Xintao Wang, Chao Dong, Xiaoou Tang, Chen Change Loy
http://arxiv.org/abs/1904.10343v1
20190423
Deep Likelihood Network for Image Restoration with Multiple Degradations
Yiwen Guo, Wangmeng Zuo, Changshui Zhang, Yurong Chen
http://arxiv.org/abs/1904.09105v1
Efficient Blind Deblurring under High Noise Levels
Jérémy Anger, Mauricio Delbracio, Gabriele Facciolo
http://arxiv.org/abs/1904.09154v1
Feature Forwarding for Efficient Single Image Dehazing
Peter Morales, Tzofi Klinghoffer, Seung Jae Lee
http://arxiv.org/abs/1904.09059v1
20190420
Generating Training Data for Denoising Real RGB Images via Camera Pipeline Simulation
Ronnachai Jaroensri, Camille Biscarrat, Miika Aittala, Frédo Durand
http://arxiv.org/abs/1904.08825v1
20190419
Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers
Jingwen He, Chao Dong, Yu Qiao
http://arxiv.org/abs/1904.08118v1
Process of image super-resolution
Sebastien Lablanche, Gerard Lablanche
http://arxiv.org/abs/1904.08396v1
20190418
A Deep Journey into Super-resolution: A survey (综述)
Saeed Anwar, Salman Khan, Nick Barnes
http://arxiv.org/abs/1904.07523v1
Real Image Denoising with Feature Attention
Saeed Anwar, Nick Barnes
http://arxiv.org/abs/1904.07396v1
20190417
Learning Deformable Kernels for Image and Video Denoising
Xiangyu Xu, Muchen Li, Wenxiu Sun
http://arxiv.org/abs/1904.06903v1
20190416
A Light Dual-Task Neural Network for Haze Removal
Yu Zhang, Xinchao Wang, Xiaojun Bi, Dacheng Tao
http://arxiv.org/abs/1904.06024v1
Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks
Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee
http://arxiv.org/abs/1904.06097v1
MAANet: Multi-view Aware Attention Networks for Image Super-Resolution
Jingcai Guo, Shiheng Ma, Song Guo
http://arxiv.org/abs/1904.06252v1
20190413
Difficulty-aware Image Super Resolution via Deep Adaptive Dual-Network
Jinghui Qin, Ziwei Xie, Yukai Shi, Wushao Wen
http://arxiv.org/abs/1904.05802v1
20190412
Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning
Ruotent Li, Loong Fah Cheong, Robby T. Tan
http://arxiv.org/abs/1904.05050v1
20190410
Blind Super-Resolution With Iterative Kernel Correction
Jinjin Gu, Hannan Lu, Wangmeng Zuo, Chao Dong
http://arxiv.org/abs/1904.03377v1
Camera Lens Super-Resolution
Chang Chen, Zhiwei Xiong, Xinmei Tian, Zheng-Jun Zha, Feng Wu
http://arxiv.org/abs/1904.03378v1
Deep Stacked Hierarchical Multi-patch Network for Image Deblurring
Hongguang Zhang, Yuchao Dai, Hongdong Li, Piotr Koniusz
http://arxiv.org/abs/1904.03468v1
20190409
Fast Spatio-Temporal Residual Network for Video Super-Resolution
Sheng Li, Fengxiang He, Bo Du, Lefei Zhang, Yonghao Xu, Dacheng Tao
http://arxiv.org/abs/1904.02870v1
Dense Haze: A benchmark for image dehazing with dense-haze and haze-free images
Codruta O. Ancuti, Cosmin Ancuti, Mateu Sbert, Radu Timofte
http://arxiv.org/abs/1904.02904v1
Blind Visual Motif Removal from a Single Image
Amir Hertz, Sharon Fogel, Rana Hanocka, Raja Giryes, Daniel Cohen-Or
http://arxiv.org/abs/1904.02756v1
20190406
Lightweight Image Super-Resolution with Adaptive Weighted Learning Network
Chaofeng Wang, Zheng Li, Jun Shi
http://arxiv.org/abs/1904.02358v1
20190404
A HVS-inspired Attention Map to Improve CNN-based Perceptual Losses for Image Restoration
Taimoor Tariq, Juan Luis Gonzalez, Munchurl Kim
https://arxiv.org/abs/1904.00205
CFSNet: Toward a Controllable Feature Space for Image Restoration
Wei Wang, Ruiming Guo, Yapeng Tian, Wenming Yang
https://arxiv.org/abs/1904.00634
Fast and Full-Resolution Light Field Deblurring using a Deep Neural Network
Jonathan Samuel Lumentut, Tae Hyun Kim, Ravi Ramamoorthi, In Kyu Park
https://arxiv.org/abs/1904.00352
Guided Super-Resolution as a Learned Pixel-to-Pixel Transformation
Riccardo de Lutio, Stefano D'Aronco, Jan Dirk Wegner, Konrad Schindler
https://arxiv.org/abs/1904.01501
PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study
Mehrdad Shoeiby, Antonio Robles-Kelly, Ran Wei, Radu Timofte
https://arxiv.org/abs/1904.00540
Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model
Jianrui Cai, Hui Zeng, Hongwei Yong, Zisheng Cao, Lei Zhang
https://arxiv.org/abs/1904.00523
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset
Tianyu Wang, Xin Yang, Ke Xu, Shaozhe Chen, Qiang Zhang, Rynson Lau
https://arxiv.org/abs/1904.01538
20190328
Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution
Lei Zhang, Zhiqiang Lang, Peng Wang, Wei Wei, Shengcai Liao, Ling Shao, Yanning Zhang
http://arxiv.org/abs/1903.10501v1
Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-Resolution Network
Esra Ataer-Cansizoglu, Michael Jones, Ziming Zhang, Alan Sullivan
http://arxiv.org/abs/1903.10974v1
20190327
Feedback Network for Image Super-Resolution
Zhen Li, Jinglei Yang, Zheng Liu, Xiaomin Yang, Gwanggil Jeon, Wei Wu
http://arxiv.org/abs/1903.09814v1
Down-Scaling with Learned Kernels in Multi-Scale Deep Neural Networks for Non-Uniform Single Image Deblurring
Dongwon Park, Jisoo Kim, Se Young Chun
http://arxiv.org/abs/1903.10157v1
Recurrent Back-Projection Network for Video Super-Resolution
Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita
http://arxiv.org/abs/1903.10128v1
Residual Non-local Attention Networks for Image Restoration
Yulun Zhang, Kunpeng Li, Kai Li, Bineng Zhong, Yun Fu
http://arxiv.org/abs/1903.10082v1
SRGAN: Training Dataset Matters
Nao Takano, Gita Alaghband
http://arxiv.org/abs/1903.09922v1
20190321
A Matrix-in-matrix Neural Network for Image Super Resolution
Hailong Ma, Xiangxiang Chu, Bo Zhang, Shaohua Wan, Bo Zhang
http://arxiv.org/abs/1903.07949v1
20190320
Proximal Splitting Networks for Image Restoration
Raied Aljadaany, Dipan K. Pal, Marios Savvides
http://arxiv.org/abs/1903.07154v1
Robust Super-Resolution GAN, with Manifold-based and Perception Loss
Uddeshya Upadhyay, Suyash P. Awate
http://arxiv.org/abs/1903.06920v1
20190316
Learning Parallax Attention for Stereo Image Super-Resolution
Longguang Wang, Yingqian Wang, Zhengfa Liang, Zaiping Lin, Jungang Yang, Wei An, Yulan Guo
http://arxiv.org/abs/1903.05784v1
Deep Residual Autoencoder for quality independent JPEG restoration
Simone Zini, Simone Bianco, Raimondo Schettini
http://arxiv.org/abs/1903.06117v1
20190315
Two-Stream Oriented Video Super-Resolution for Action Recognition
Haochen Zhang, Dong Liu, Zhiwei Xiong
http://arxiv.org/abs/1903.05577v1
20190308
Photo-realistic Image Super-resolution with Fast and Lightweight Cascading Residual Network
Namhyuk Ahn, Byungkon Kang, Kyung-Ah Sohn
http://arxiv.org/abs/1903.02240v1
20190306
An Adversarial Super-Resolution Remedy for Radar Design Trade-offs
Sherif Abdulatif, Karim Armanious, Fady Aziz, Urs Schneider, Bin Yang
http://arxiv.org/abs/1903.01392v1
Meta-SR: A Magnification-Arbitrary Network for Super-Resolution
Xuecai Hu, Haoyuan Mu, Xiangyu Zhang, Zilei Wang, Jian Sun, Tieniu Tan
http://arxiv.org/abs/1903.00875v1
Image Super-Resolution by Neural Texture Transfer
Zhifei Zhang, Zhaowen Wang, Zhe Lin, Hairong Qi
http://arxiv.org/abs/1903.00834v1
Extreme Channel Prior Embedded Network for Dynamic Scene Deblurring
Jianrui Cai, Wangmeng Zuo, Lei Zhang
http://arxiv.org/abs/1903.00763v1
20190305
Deep Learning for Multiple-Image Super-Resolution
Michal Kawulok, Pawel Benecki, Szymon Piechaczek, Krzysztof Hrynczenko, Daniel Kostrzewa, Jakub Nalepa
http://arxiv.org/abs/1903.00440v1
GAN Based Image Deblurring Using Dark Channel Prior
Shuang Zhang, Ada Zhen, Robert L. Stevenson
http://arxiv.org/abs/1903.00107v1
Single Image Deblurring and Camera Motion Estimation with Depth Map
Liyuan Pan, Yuchao Dai, Miaomiao Liu
http://arxiv.org/abs/1903.00231v1
Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks
Joshua Peter Ebenezer, Bijaylaxmi Das, Sudipta Mukhopadhyay
http://arxiv.org/abs/1903.00395v1
20190302
Two-phase Hair Image Synthesis by Self-Enhancing Generative Model
Haonan Qiu, Chuan Wang, Hang Zhu, Xiangyu Zhu, Jinjin Gu, Xiaoguang Han
http://arxiv.org/abs/1902.11203v1
20190220
Deep Learning for Image Super-resolution: A Survey
Zhihao Wang, Jian Chen, Steven C. H. Hoi
http://arxiv.org/abs/1902.06068v1
20190219
Breaking the Spatio-Angular Trade-off for Light Field Super-Resolution via LSTM Modelling on Epipolar Plane Images
Hao Zhu, Mantang Guo, Hongdong Li, Qing Wang, Antonio Robles-Kelly
http://arxiv.org/abs/1902.05672v1
Lightweight Feature Fusion Network for Single Image Super-Resolution
Wenming Yang, Wei Wang, Xuechen Zhang, Shuifa Sun, Qingmin Liao
http://arxiv.org/abs/1902.05694v1
20190218
On instabilities of deep learning in image reconstruction - Does AI come at a cost?
Vegard Antun, Francesco Renna, Clarice Poon, Ben Adcock, Anders C. Hansen
http://arxiv.org/abs/1902.05300v1
Deep HVS-IQA Net: Human Visual System Inspired Deep Image Quality Assessment Networks
Soomin Seo, Sehwan Ki, Munchurl Kim
http://arxiv.org/abs/1902.05316v1
20190215
Super-Resolution of Brain MRI Images using Overcomplete Dictionaries and Nonlocal Similarity
Yinghua Li, Bin Song, Jie Guo, Xiaojiang Du, Mohsen Guizani
http://arxiv.org/abs/1902.04902v1
20190209
Advances on CNN-based super-resolution of Sentinel-2 images
Massimiliano Gargiulo
http://arxiv.org/abs/1902.02513v1
Theoretical analysis on Noise2Noise using Stein's Unbiased Risk Estimator for Gaussian denoising: Towards unsupervised training with clipped noisy images
Magauiya Zhussip, Shakarim Soltanayev, Se Young Chun
http://arxiv.org/abs/1902.02452v1
20190206
End-to-End Single Image Fog Removal using Enhanced Cycle Consistent Adversarial Networks
Wei Liu, Xianxu Hou, Jiang Duan, Guoping Qiu
http://arxiv.org/abs/1902.01374v1
Night Time Haze and Glow Removal using Deep Dilated Convolutional Network
Shiba Kuanar, K. R. Rao, Dwarikanath Mahapatra, Monalisa Bilas
http://arxiv.org/abs/1902.00855v1
20190205
Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution
Oleksii Sidorov, Jon Yngve Hardeberg
http://arxiv.org/abs/1902.00301v1
Generative Smoke Removal
Oleksii Sidorov, Congcong Wang, Faouzi Alaya Cheikh
http://arxiv.org/abs/1902.00311v1
20190202
Resolution enhancement in scanning electron microscopy using deep learning
Kevin de Haan, Zachary S. Ballard, Yair Rivenson, Yichen Wu, Aydogan Ozcan
http://arxiv.org/abs/1901.11094v1
Noise2Self: Blind Denoising by Self-Supervision
Joshua Batson, Loic Royer
http://arxiv.org/abs/1901.11365v1
20190124
Adversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy
Daniele Ravì, Agnieszka Barbara Szczotka, Stephen P Pereira, Tom Vercauteren
http://arxiv.org/abs/1901.06988v1
Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search
Xiangxiang Chu, Bo Zhang, Hailong Ma, Ruijun Xu, Jixiang Li, Qingyuan Li
http://arxiv.org/abs/1901.07261v1
20190122
Generative Adversarial Classifier for Handwriting Characters Super-Resolution
Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Jimin Xiao, Rui Zhang
http://arxiv.org/abs/1901.06199v1
Linearized ADMM and Fast Nonlocal Denoising for Efficient Plug-and-Play Restoration
Unni V. S., Sanjay Ghosh, Kunal N. Chaudhury
http://arxiv.org/abs/1901.06110v1
20190119
Foreground-aware Image Inpainting
Wei Xiong, Zhe Lin, Jimei Yang, Xin Lu, Connelly Barnes, Jiebo Luo
http://arxiv.org/abs/1901.05945v1
Image Enhancement Network Trained by Using HDR images
Yuma Kinoshita, Hitoshi Kiya
http://arxiv.org/abs/1901.05686v1
20190110
Morphological Networks for Image De-raining
Ranjan Mondal, Pulak Purkait, Sanchayan Santra, Bhabatosh Chanda
http://arxiv.org/abs/1901.02411v1
20190109
On the Global Geometry of Sphere-Constrained Sparse Blind Deconvolution
Yuqian Zhang, Yenson Lau, Han-Wen Kuo, Sky Cheung, Abhay Pasupathy, John Wright
http://arxiv.org/abs/1901.01913v1
Blind Motion Deblurring with Cycle Generative Adversarial Networks
Quan Yuan, Junxia Li, Lingwei Zhang, Zhefu Wu, Guangyu Liu
http://arxiv.org/abs/1901.01641v1
Image Super-Resolution as a Defense Against Adversarial Attacks
Aamir Mustafa, Salman H. Khan, Munawar Hayat, Jianbing Shen, Ling Shao
http://arxiv.org/abs/1901.01677v1
20190104
EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning
Kamyar Nazeri, Eric Ng, Tony Joseph, Faisal Qureshi, Mehran Ebrahimi
http://arxiv.org/abs/1901.00212v1
20190102
Brain MRI super-resolution using 3D generative adversarial networks
Irina Sanchez, Veronica Vilaplana
http://arxiv.org/abs/1812.11440v1
Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse Coding
Menglei Zhang, Zhou Liu, Lei Yu
http://arxiv.org/abs/1812.11950v1
Fast Perceptual Image Enhancement
Etienne de Stoutz, Andrey Ignatov, Nikolay Kobyshev, Radu Timofte, Luc Van Gool
http://arxiv.org/abs/1812.11852v1
CFA Bayer image sequence denoising and demosaicking chain
Antoni Buades, Joan Duran
http://arxiv.org/abs/1812.11207v1
Total Variation with Overlapping Group Sparsity and Lp Quasinorm for Infrared Image Deblurring under Salt-and-Pepper Noise
Xingguo Liua, Yinping Chena, Zhenming Penga, Juan Wu
http://arxiv.org/abs/1812.11725v1
20190101
Adaptive Image Sampling using Deep Learning and its Application on X-Ray Fluorescence Image Reconstruction
Qiqin Dai, Henry Chopp, Emeline Pouyet, Oliver Cossairt, Marc Walton, Aggelos K. Katsaggelos
http://arxiv.org/abs/1812.10836v1
20181228
Motion Blur removal via Coupled Autoencoder
Kavya Gupta, Brojeshwar Bhowmick, Angshul Majumdar
http://arxiv.org/abs/1812.09888v1
Perceptually-based single-image depth super-resolution
O. Voinov, A. Artemov, V. Egiazarian, A. Notchenko, G. Bobrovskikh, D. Zorin, E. Burnaev
http://arxiv.org/abs/1812.09874v1
20181225
3DSRnet: Video Super-resolution using 3D Convolutional Neural Networks
Soo Ye Kim, Jeongyeon Lim, Taeyoung Na, Munchurl Kim
http://arxiv.org/abs/1812.09079v1
A Multiscale Image Denoising Algorithm Based On Dilated Residual Convolution Network
Chang Liu, Zhaowei Shang, Anyong Qin
http://arxiv.org/abs/1812.09131v1
20181222
Rain Removal By Image Quasi-Sparsity Priors
Yinglong Wang, Shuaicheng Liu, Chen Chen, Dehua Xie, Bing Zeng
http://arxiv.org/abs/1812.08348v1
20181220
Hybrid Loss for Learning Single-Image-based HDR Reconstruction
Kenta Moriwaki, Ryota Yoshihashi, Rei Kawakami, Shaodi You, Takeshi Naemura
http://arxiv.org/abs/1812.07134v1
SREdgeNet: Edge Enhanced Single Image Super Resolution using Dense Edge Detection Network and Feature Merge Network
Kwanyoung Kim, Se Young Chun
http://arxiv.org/abs/1812.07174v1
20181219
Efficient Super Resolution Using Binarized Neural Network
Yinglan Ma, Hongyu Xiong, Zhe Hu, Lizhuang Ma
http://arxiv.org/abs/1812.06378v1
High-Resolution Talking Face Generation via Mutual Information Approximation
Hao Zhu, Aihua Zheng, Huaibo Huang, Ran He
http://arxiv.org/abs/1812.06589v1
20181218
Advanced Super-Resolution using Lossless Pooling Convolutional Networks
Farzad Toutounchi, Ebroul Izquierdo
http://arxiv.org/abs/1812.06023v1
20181217
Binary Document Image Super Resolution for Improved Readability and OCR Performance
R K Pandey, K Vignesh, A G Ramakrishnan, C B
https://www.researchgate.net/publication/329465039_Binary_Document_Image_Super_Resolution_for_Improved_Readability_and_OCR_Performance
20181215
Unsupervised Degradation Learning for Single Image Super-Resolution
Tianyu Zhao, Wenqi Ren, Changqing Zhang, Dongwei Ren, Qinghua Hu
http://arxiv.org/abs/1812.04240v2
Wider Channel Attention Network for Remote Sensing Image Super-resolution
Jun Gu, Guangluan Xu, Yue Zhang, Xian Sun, Ran Wen, Lei Wang
http://arxiv.org/abs/1812.05329v1
20181214
Efficient Super Resolution For Large-Scale Image Using Attentional GAN
Harsh Nilesh Pathak, Xinxin Li, Shervin Minaee, Brooke Cowan
http://arxiv.org/abs/1812.04821v1
20181213
Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising
Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao
http://arxiv.org/abs/1812.04243v1
Supervised Deep Kriging for Single-Image Super-Resolution
Gianni Franchi, Angela Yao, Andreas Kolb
http://arxiv.org/abs/1812.04042v1
The Effects of Super-Resolution on Object Detection Performance in Satellite Imagery
Jacob Shermeyer, Adam Van Etten
http://arxiv.org/abs/1812.04098v1
Unsupervised Degradation Learning for Single Image Super-Resolution
Tianyu Zhao, Changqing Zhang, Wenqi Ren, Dongwei Ren, Qinghua Hu
http://arxiv.org/abs/1812.04240v1
20181212
Feature Denoising for Improving Adversarial Robustness
Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan Yuille, Kaiming He
http://arxiv.org/abs/1812.03411v1
Unsupervised Learning of Monocular Depth Estimation with Bundle Adjustment, Super-Resolution and Clip Loss
Lipu Zhou, Jiamin Ye, Montiel Abello, Shengze Wang, Michael Kaess
http://arxiv.org/abs/1812.03368v1
20181211
Neural Image Decompression: Learning to Render Better Image Previews
Shumeet Baluja, Dave Marwood, Nick Johnston, Michele Covell
http://arxiv.org/abs/1812.02831v1
TDAN: Temporally Deformable Alignment Network for Video Super-Resolution
Yapeng Tian, Yulun Zhang, Yun Fu, Chenliang Xu
http://arxiv.org/abs/1812.02898v1
Variational Saccading: Efficient Inference for Large Resolution Images
Jason Ramapuram, Maurits Diephuis, Russ Webb, Alexandros Kalousis
http://arxiv.org/abs/1812.03170v1
20181208
Faster Neural Networks Straight from JPEG
L Gueguen, A Sergeev, B Kadlec, R Liu, J Yosinski
https://openreview.net/forum?id=S1ry6Y1vG
Binary Document Image Super Resolution for Improved Readability and OCR Performance
Ram Krishna Pandey, K Vignesh, A G Ramakrishnan, Chandrahasa B
http://arxiv.org/abs/1812.02475v1
20181207
Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling
Jacob Menick, Nal Kalchbrenner
http://arxiv.org/abs/1812.01608v1
20181204
An Efficient Image Retrieval Based on Fusion of Low-Level Visual Features
Atif Nazir, Kashif Nazir
http://arxiv.org/abs/1811.12695v1
Super-Resolution based on Image-Adapted CNN Denoisers: Incorporating Generalization of Training Data and Internal Learning in Test Time
Tom Tirer, Raja Giryes
http://arxiv.org/abs/1811.12866v1
20181128
Deep Laplacian Pyramid Network for Text Images Super-Resolution
Hanh T. M. Tran, Tien Ho-Phuoc
http://arxiv.org/abs/1811.10449v1
20181127
Temporally Coherent GANs for Video Super-Resolution (TecoGAN)
Mengyu Chu, You Xie, Laura Leal-Taixé, Nils Thuerey
http://arxiv.org/abs/1811.09393v1
Spatio-Temporal Road Scene Reconstruction using Superpixel MRF
Yaochen Li, Yuehu Liu, Jihua Zhu, Shiqi Ma, Zhenning Niu, Rui Guo
http://arxiv.org/abs/1811.09790v1
20171217
"Zero-Shot" Super-Resolution using Deep Internal Learning
Assaf Shocher, Nadav Cohen, Michal Irani
https://arxiv.org/abs/1712.06087v1
【其他网站Super-resolution文献等资源】
Github:https://github.com/YapengTian/Single-Image-Super-Resolution
有任何问题可联系作者Hawk,邮箱:yangzhanyuan@std.uestc.edu.cn
好运常伴。