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This paper proposes a novel approach to regularize the \textit{ill-posed} and \textit{non-linear} blind image deconvolution (blind deblurring) using deep generative networks as priors.
A. Levin, Y. Weiss, F. Durand, and W. T. Freeman, “Understanding and evaluating blind deconvolution algorithms,” in Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on . IEEE, 2009, pp. 1964–1971
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T. F. Chan and C.-K. Wong, “Total variation blind deconvolution,” IEEE transactions on Image Processing , vol. 7, no. 3, pp. 370–375, 1998
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Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE transactions on image processing , vol. 13, no. 4, pp. 600–612, 2004
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R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, and W. T. Freeman, “Removing camera shake from a single photograph,” in ACM transactions on graphics (TOG) , vol. 25, no. 3. ACM, 2006, pp. 787–794
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D. Krishnan and R. Fergus, “Fast image deconvolution using hyper-laplacian priors,” in Advances in Neural Information Processing Systems , 2009, pp. 1033–1041
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J.-F. Cai, H. Ji, C. Liu, and Z. Shen, “Blind motion deblurring from a single image using sparse approximation,” in Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on . IEEE, 2009, pp. 104–111
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Z. Hu, J.-B. Huang, and M.-H. Yang, “Single image deblurring with adaptive dictionary learning,” in Image Processing (ICIP), 2010 17th IEEE International Conference on . IEEE, 2010, pp. 1169–1172
2010
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H. Zhang, J. Yang, Y. Zhang, and T. S. Huang, “Sparse representation based blind image deblurring,” in Multimedia and Expo (ICME), 2011 IEEE International Conference on . IEEE, 2011, pp. 1–6
2011
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L. Xu, C. Lu, Y. Xu, and J. Jia, “Image smoothing via l 0 gradient minimization,” in ACM Transactions on Graphics (TOG) , vol. 30, no. 6. ACM, 2011, p. 174
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G. Boracchi, A. Foi et al. , “Modeling the performance of image restoration from motion blur.” IEEE Trans. Image Processing , vol. 21, no. 8, pp. 3502–3517, 2012
2012
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L. Xu, S. Zheng, and J. Jia, “Unnatural l0 sparse representation for natural image deblurring,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2013, pp. 1107–1114
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2013
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T. Michaeli and M. Irani, “Blind deblurring using internal patch recurrence,” in European Conference on Computer Vision . Springer, 2014, pp. 783–798
2014
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A. Ahmed, B. Recht, and J. Romberg, “Blind deconvolution using convex programming,” IEEE Transactions on Information Theory , vol. 60, no. 3, pp. 1711–1732, 2014
2014
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J. Pan, R. Liu, Z. Su, and G. Liu, “Motion blur kernel estimation via salient edges and low rank prior,” in Multimedia and Expo (ICME), 2014 IEEE International Conference on . IEEE, 2014, pp. 1–6
2014
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I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in Advances in neural information processing systems , 2014, pp. 2672–2680
2014
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A. Yu and K. Grauman, “Fine-grained visual comparisons with local learning,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2014, pp. 192–199
2014
Cited alongside, same era.
M. Hradiš, J. Kotera, P. Zemcík, and F. Šroubek, “Convolutional neural networks for direct text deblurring,” in Proceedings of BMVC , vol. 10, 2015
2015
Cited alongside, same era.
P. Campisi and K. Egiazarian, Blind image deconvolution: theory and applications . CRC press, 2016
2016
Cited alongside, same era.
W. Ren, X. Cao, J. Pan, X. Guo, W. Zuo, and M.-H. Yang, “Image deblurring via enhanced low-rank prior,” IEEE Transactions on Image Processing , vol. 25, no. 7, pp. 3426–3437, 2016
2016
Cited alongside, same era.
C. J. Schuler, M. Hirsch, S. Harmeling, and B. Schölkopf, “Learning to deblur,” IEEE transactions on pattern analysis and machine intelligence , vol. 38, no. 7, pp. 1439–1451, 2016
T. Nimisha, A. K. Singh, and A. Rajagopalan, “Blur-invariant deep learning for blind-deblurring,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 4752–4760
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
R. A. Yeh, C. Chen, T. Y. Lim, A. G. Schwing, M. Hasegawa-Johnson, and M. N. Do, “Semantic image inpainting with deep generative models,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 5485–5493
2017
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2016
Cited alongside, same era.
A. Chakrabarti, “A neural approach to blind motion deblurring,” in European Conference on Computer Vision . Springer, 2016, pp. 221–235
2016
Cited alongside, same era.
P. Svoboda, M. Hradiš, L. Maršík, and P. Zemcík, “Cnn for license plate motion deblurring,” in Image Processing (ICIP), 2016 IEEE International Conference on . IEEE, 2016, pp. 3832–3836
2016
Cited alongside, same era.
J. Pan, D. Sun, H. Pfister, and M.-H. Yang, “Blind image deblurring using dark channel prior,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 1628–1636
2016
Cited alongside, same era.
2016
Cited alongside, same era.
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen, “Improved techniques for training gans,” in Advances in Neural Information Processing Systems , 2016, pp. 2234–2242
2016
Cited alongside, same era.
2016
Cited alongside, same era.
2017
Cited alongside, same era.
2017
Later among the works it cites.
A. Srivastava, L. Valkov, C. Russell, M. U. Gutmann, and C. Sutton, “Veegan: Reducing mode collapse in gans using implicit variational learning,” in Advances in Neural Information Processing Systems , 2017, pp. 3308–3318
2017
Later among the works it cites.
2017
Later among the works it cites.
L. Li, J. Pan, W.-S. Lai, C. Gao, N. Sang, and M.-H. Yang, “Learning a discriminative prior for blind image deblurring,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 6616–6625
2018
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Y. Chen, F. Wu, and J. Zhao, “Motion deblurring via using generative adversarial networks for space-based imaging,” in 2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA) . IEEE, 2018, pp. 37–41
2018
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2018
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P. Hand, O. Leong, and V. Voroninski, “Phase retrieval under a generative prior,” in Advances in Neural Information Processing Systems , 2018, pp. 9154–9164
2018
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2018
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P. Samangouei, M. Kabkab, and R. Chellappa, “Defense-gan: Protecting classifiers against adversarial attacks using generative models,” 2018
2018
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S. Athar, E. Burnaev, and V. Lempitsky, “Latent convolutional models,” 2018
2018
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