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Is it possible to recover an image from its noisy version using convolutional neural networks? This is an interesting problem as convolutional layers are generally used as feature detectors for tasks like classification, segmentation and object detection.
Products of experts
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Image denoising using scale mixtures of gaussians in the wavelet domain
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A review of image denoising algorithms, with a new one
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V. Jain and S. Seung · 2009
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Eq. indoor scenes
A. Quattoni and A. Torralba · 2009
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The PASCAL Visual Object Classes Challenge 2011 (VOC2011) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2011
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From learning models of natural image patches to whole image restoration
D. Zoran and Y. Weiss · 2011
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Image denoising: Can plain neural networks compete with bm3d?
H. C. Burger, C. J. Schuler, and S. Harmeling · 2012
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Weighted nuclear norm minimization with application to image denoising
S. Gu, L. Zhang, W. Zuo, and X. Feng · 2014
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Learning deep features for scene recognition using places database
B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva · 2014
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Deep generative image models using a laplacian pyramid of adversarial networks
E. L. Denton, S. Chintala, R. Fergus, et al · 2015
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A neural algorithm of artistic style
L. A. Gatys, A. S. Ecker, and M. Bethge · 2015
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Deep multi-scale video prediction beyond mean square error
M. Mathieu, C. Couprie, and Y. LeCun · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
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D. P. Kingma and J. Ba · 2014
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Shrinkage fields for effective image restoration
U. Schmidt and S. Roth · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
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Photo-realistic single image super-resolution using a generative adversarial network
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Improved techniques for training gans
T. Salimans, I. J. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
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Deep gaussian conditional random field network: A model-based deep network for discriminative denoising
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