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In the last few years, image denoising has benefited a lot from the fast development of neural networks.
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
David Martin, Charless Fowlkes, Doron Tal, and Jitendra Malik · 2001
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A non-local algorithm for image denoising
Antoni Buades, Bartomeu Coll, and J-M Morel · 2005
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Image denoising by sparse 3-d transform-domain collaborative filtering
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Optimal inversion of the anscombe transformation in low-count poisson image denoising
Markku Makitalo and Alessandro Foi · 2010
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On single image scale-up using sparse-representations
Roman Zeyde, Michael Elad, and Matan Protter · 2010
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Weighted nuclear norm minimization with application to image denoising
Shuhang Gu, Lei Zhang, Wangmeng Zuo, and Xiangchu Feng · 2014
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An efficient statistical method for image noise level estimation
Guangyong Chen, Fengyuan Zhu, and Pheng Ann Heng · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections
Xiaojiao Mao, Chunhua Shen, and Yu-Bin Yang · 2016
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Memnet: A persistent memory network for image restoration
Ying Tai, Jian Yang, Xiaoming Liu, and Chunyan Xu · 2017
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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2017
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A high-quality denoising dataset for smartphone cameras
Abdelrahman Abdelhamed, Stephen Lin, and Michael S Brown · 2018
Cited alongside, same era.
Universal denoising networks : A novel cnn architecture for image denoising
Stamatios Lefkimmiatis · 2018
Cited alongside, same era.
Noise2noise: Learning image restoration without clean data
Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, and Timo Aila · 2018
Cited alongside, same era.
When image denoising meets high-level vision tasks: A deep learning approach
Ding Liu, Bihan Wen, Xianming Liu, Zhangyang Wang, and Thomas Huang · 2018
Cited alongside, same era.
Neural nearest neighbors networks
Tobias Plötz and Stefan Roth · 2018
Cited alongside, same era.
Training deep learning based denoisers without ground truth data
Shakarim Soltanayev and Se Young Chun · 2018
Noise2void - learning denoising from single noisy images
Alexander Krull, Tim-Oliver Buchholz, and Florian Jug · 2019
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Probabilistic noise2void: Unsupervised content-aware denoising
Alexander Krull, Tomas Vicar, and Florian Jug · 2019
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High-quality self-supervised deep image denoising
Samuli Laine, Tero Karras, Jaakko Lehtinen, and Timo Aila · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Magauiya Zhussip, Shakarim Soltanayev, and Se Young Chun · 2019
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Cited alongside, same era.
Deep image prior
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2018
Cited alongside, same era.
Ffdnet: Toward a fast and flexible solution for cnn-based image denoising
Kai Zhang, Wangmeng Zuo, and Lei Zhang · 2018
Cited alongside, same era.
Noise2self: Blind denoising by self-supervision
Joshua Batson and Loic Royer · 2019
Cited alongside, same era.
Fully convolutional pixel adaptive image denoiser
Sungmin Cha and Taesup Moon · 2019
Cited alongside, same era.
Self-guided network for fast image denoising
Shuhang Gu, Yawei Li, Luc Van Gool, and Radu Timofte · 2019
Cited alongside, same era.
Toward convolutional blind denoising of real photographs
Shi Guo, Zifei Yan, Kai Zhang, Wangmeng Zuo, and Lei Zhang · 2019
Cited alongside, same era.
https://www.eecs.yorku.ca/~kamel/sidd/benchmark.php
Abdelrahman Abdelhamed · 2020
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Noisier2noise: Learning to denoise from unpaired noisy data
Nick Moran, Dan Schmidt, Yu Zhong, and Patrick Coady · 2020
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Self2self with dropout: Learning self-supervised denoising from single image
Yuhui Quan, Mingqin Chen, Tongyao Pang, and Hui Ji · 2020
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Unpaired learning of deep image denoising
Xiaohe Wu, Ming Liu, Yue Cao, Dongwei Ren, and Wangmeng Zuo · 2020
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Noisy-as-clean: Learning self-supervised denoising from corrupted image
Jun Xu, Yuan Huang, Ming-Ming Cheng, Li Liu, Fan Zhu, Zhou Xu, and Ling Shao · 2020
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Cycleisp: Real image restoration via improved data synthesis
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, and Ling Shao · 2020
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