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This paper proposes a new way of regularizing an inverse problem in imaging (e.g., deblurring or inpainting) by means of a deep generative neural network.
“Nonlinear total variation based noise removal algorithms,”
L. I. Rudin, S. Osher, and E. Fatemi, · 1992
Earlier work this paper cites.
“K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation,”
M. Aharon, M. Elad, and A. Bruckstein, · 2006
Earlier work this paper cites.
“Image denoising by sparse 3-D transform-domain collaborative filtering,”
K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, · 2007
Earlier work this paper cites.
“Analysis versus synthesis in signal priors,”
M. Elad, P. Milanfar, and R. Rubinstein, · 2007
Earlier work this paper cites.
“Total generalized variation,”
K. Bredies, K. Kunisch, and T. Pock, · 2010
Earlier work this paper cites.
“Optimal inversion of the generalized Anscombe transformation for Poisson-Gaussian noise,”
M. Makitalo and A. Foi, · 2012
Earlier work this paper cites.
Bayesian approach to inverse problems
J. Idier, · 2013
Earlier work this paper cites.
“Plug-and-play priors for model based reconstruction,”
S. V. Venkatakrishnan, C. A. Bouman, and B. Wohlberg, · 2013
Earlier work this paper cites.
“The cosparse analysis model and algorithms,”
S. Nam, M. E. Davies, M. Elad, and R. Gribonval, · 2013
Earlier work this paper cites.
“Auto-encoding variational Bayes,”
D. P. Kingma and M. Welling, · 2014
Earlier work this paper cites.
“Stochastic backpropagation and approximate inference in deep generative models,”
D. J. Rezende, S. Mohamed, and D. Wierstra, · 2014
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“Nice: Non-linear independent components estimation,”
L. Dinh, D. Krueger, and Y. Bengio, · 2014
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“Plug-and-play ADMM for image restoration: Fixed-point convergence and applications,”
S. H. Chan, X. Wang, and O. A. Elgendy, · 2016
Cited alongside, same era.
“Improved variational inference with inverse autoregressive flow,”
D. P. Kingma, T. Salimans, R. Jozefowicz, X. Chen, I. Sutskever, and M. Welling, · 2016
Cited alongside, same era.
“Learning deep CNN denoiser prior for image restoration,”
K. Zhang, W. Zuo, S. Gu, and L. Zhang, · 2017
Cited alongside, same era.
“Generative image inpainting with contextual attention,”
J. Yu, Z. Lin, J. Yang, X. Shen, X. Lu, and T. S. Huang, · 2018
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“Glow: Generative flow with invertible 1x1 convolutions,”
D. P. Kingma and P. Dhariwal, · 2018
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“Large-scale celebfaces attributes (celeba) dataset,”
Z. Liu, P. Luo, X. Wang, and X. Tang, · 2018
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“Solving inverse problems using data-driven models,”
S. Arridge, P. Maass, O. Öktem, and C-B. Schönlieb, · 2019
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“Solving inverse problems by joint posterior maximization with a VAE prior,”
M. Gonzalez, A. Almansa, M. Delbracio, P. Musé, and P. Tan, · 2019
Later among the works it cites.
Introduction to inverse problems in imaging
M. Bertero, · 2020
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J.H. Rick Chang, C.-L. Li, B. Poczos, B.V.K. Vijaya Kumar, and A. C. Sankaranarayanan, · 2017
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“Compressed sensing using generative models,”
A. Bora, A. Jalal, E. Price, and A. G. Dimakis, · 2017
Cited alongside, same era.
“FFDNet: Toward a fast and flexible solution for CNN-based image denoising,”
K. Zhang, W. Zuo, and L. Zhang, · 2018
Cited alongside, same era.
“Deep image prior,”
D. Ulyanov, A. Vedaldi, and V. Lempitsky, · 2018
Cited alongside, same era.
“Deep unfolding of a proximal interior point method for image restoration,”
C. Bertocchi, E. Chouzenoux, M-C. Corbineau, J-C. Pesquet, and M. Prato,
Cited in the paper.
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“Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling,”
E. Monier, T. Oberlin, N. Brun, X. Li, M. Tencé, and N. Dobigeon, · 2020
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“Invertible generative models for inverse problems: mitigating representation error and dataset bias,”
M. Asim, A. Ahmed, and P. Hand, · 2020
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“Robust compressed sensing of generative models,”
A. Jalal, L. Liu, A. G. Dimakis, and C. Caramanis, · 2020
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