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Deep image prior (DIP), which utilizes a deep convolutional network (ConvNet) structure itself as an image prior, has attracted attentions in computer vision and machine learning communities.
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A rank minimization approach to video inpainting
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Structured low-rank approximation and its applications
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Extracting and composing robust features with denoising autoencoders
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Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation
A. Cichocki, R. Zdunek, A. H. Phan, and S.-i. Amari · 2009
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Manifold models for signals and images
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Robust video denoising using low rank matrix completion
H. Ji, C. Liu, Z. Shen, and Y. Xu · 2010
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Tensor completion for estimating missing values in visual data
J. Liu, P. Musialski, P. Wonka, and J. Ye · 2013
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PET image reconstruction using deep image prior
K. Gong, C. Catana, J. Qi, and Q. Li · 2018
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Deep decoder: Concise image representations from untrained non-convolutional networks
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Noise2noise: Learning image restoration without clean data
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Blind denoising autoencoder
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Feature extraction for incomplete data via low-rank tensor decomposition with feature regularization
Q. Shi, Y.-M. Cheung, Q. Zhao, and H. Lu · 2018
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Zero-shot super-resolution using deep internal learning
A. Shocher, N. Cohen, and M. Irani · 2018
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What regularized auto-encoders learn from the data-generating distribution
G. Alain and Y. Bengio · 2014
Cited alongside, same era.
Auto-encoding variational bayes
M. W. Diederik P Kingma · 2014
Cited alongside, same era.
Weighted nuclear norm minimization with application to image denoising
S. Gu, L. Zhang, W. Zuo, and X. Feng · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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Group-based sparse representation for image restoration
J. Zhang, D. Zhao, and W. Gao · 2014
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Novel methods for multilinear data completion and de-noising based on tensor-SVD
Z. Zhang, G. Ely, S. Aeron, N. Hao, and M. Kilmer · 2014
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Deep image prior
D. Ulyanov, A. Vedaldi, and V. Lempitsky · 2018
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Compressed sensing with deep image prior and learned regularization
D. Van Veen, A. Jalal, M. Soltanolkotabi, E. Price, S. Vishwanath, and A. G. Dimakis · 2018
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A fused cp factorization method for incomplete tensors
Y. Wu, H. Tan, Y. Li, J. Zhang, and X. Chen · 2018
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Multi-scale weighted nuclear norm image restoration
N. Yair and T. Michaeli · 2018
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Missing slice recovery for tensors using a low-rank model in embedded space
T. Yokota, B. Erem, S. Guler, S. K. Warfield, and H. Hontani · 2018
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A nonconvex relaxation approach to low-rank tensor completion
X. Zhang · 2018
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Noise2self: Blind denoising by self-supervision
J. Batson and L. Royer · 2019
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Gan2gan: Generative noise learning for blind image denoising with single noisy images
S. Cha, T. Park, and T. Moon · 2019
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”double-dip”: Unsupervised image decomposition via coupled deep-image-priors
Y. Gandelsman, A. Shocher, and M. Irani · 2019
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Noise2void-learning denoising from single noisy images
A. Krull, T.-O. Buchholz, and F. Jug · 2019
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Self-supervised deep image denoising
S. Laine, J. Lehtinen, and T. Aila · 2019
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Singan: Learning a generative model from a single natural image
T. R. Shaham, T. Dekel, and T. Michaeli · 2019
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Ingan: Capturing and retargeting the DNA of a natural image
A. Shocher, S. Bagon, P. Isola, and M. Irani · 2019
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Deep geometric prior for surface reconstruction
F. Williams, T. Schneider, C. Silva, D. Zorin, J. Bruna, and D. Panozzo · 2019
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Noisy-as-clean: Learning unsupervised denoising from the corrupted image
J. Xu, Y. Huang, L. Liu, F. Zhu, X. Hou, and L. Shao · 2019
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Enhanced sparsity prior model for low-rank tensor completion
J. Xue, Y. Zhao, W. Liao, J. C.-W. Chan, and S. G. Kong · 2019
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Simultaneous tensor completion and denoising by noise inequality constrained convex optimization
T. Yokota and H. Hontani · 2019
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Dynamic PET image reconstruction using nonnegative matrix factorization incorporated with deep image prior
T. Yokota, K. Kawai, M. Sakata, Y. Kimura, and H. Hontani · 2019
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Accurate tensor completion via adaptive low-rank representation
L. Zhang, W. Wei, Q. Shi, C. Shen, A. van den Hengel, and Y. Zhang · 2019
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