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Conventionally, image denoising and high-level vision tasks are handled separately in computer vision.
K-SVD : An algorithm for designing overcomplete dictionaries for sparse representation
Michal Aharon, Michael Elad, and Alfred Bruckstein · 2006
Earlier work this paper cites.
Color image denoising via sparse 3d collaborative filtering with grouping constraint in luminance-chrominance space
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
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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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Scope of validity of psnr in image/video quality assessment
Quan Huynh-Thu and Mohammed Ghanbari · 2008
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Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
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Non-local sparse models for image restoration
J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman · 2009
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From learning models of natural image patches to whole image restoration
Daniel Zoran and Yair Weiss · 2011
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Image denoising: Can plain neural networks compete with bm3d?
Harold C Burger, Christian J Schuler, and Stefan Harmeling · 2012
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Nonlocally centralized sparse representation for image restoration
Weisheng Dong, Lei Zhang, Guangming Shi, and Xin Li · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Semantic image segmentation with deep convolutional nets and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2014
Cited alongside, same era.
Weighted nuclear norm minimization with application to image denoising
Shuhang Gu, Lei Zhang, Wangmeng Zuo, and Xiangchu Feng · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
Anh Nguyen, Jason Yosinski, and Jeff Clune · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Cited alongside, same era.
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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Studying very low resolution recognition using deep networks
Zhangyang Wang, Shiyu Chang, Yingzhen Yang, Ding Liu, and Thomas S Huang · 2016
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Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration
Yunjin Chen and Thomas Pock · 2017
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Aod-net: All-in-one dehazing network
Boyi Li, Xiulian Peng, Zhangyang Wang, Jizheng Xu, and Dan Feng · 2017
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Enhance visual recognition under adverse conditions via deep networks
Ding Liu, Bowen Cheng, Zhangyang Wang, Haichao Zhang, and Thomas S Huang · 2017
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Patch group based nonlocal self-similarity prior learning for image denoising
Jun Xu, Lei Zhang, Wangmeng Zuo, David Zhang, and Xiangchu Feng · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
Cited alongside, same era.
Robust single image super-resolution via deep networks with sparse prior
Ding Liu, Zhaowen Wang, Bihan Wen, Jianchao Yang, Wei Han, and Thomas S Huang · 2016
Cited alongside, same era.
Jiqing Wu, Radu Timofte, Zhiwu Huang, and Luc Van Gool · 2017
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Multi-channel weighted nuclear norm minimization for real color image denoising
Jun Xu, Lei Zhang, David Zhang, and Xiangchu Feng · 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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Learning deep cnn denoiser prior for image restoration
Kai Zhang, Wangmeng Zuo, Shuhang Gu, and Lei Zhang · 2017
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