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Non-uniform blind deblurring for general dynamic scenes is a challenging computer vision problem as blurs arise not only from multiple object motions but also from camera shake, scene depth variation.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Single image deblurring using motion density functions
A. Gupta, N. Joshi, C. L. Zitnick, M. Cohen, and B. Curless · 2010
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Space-variant single-image blind deconvolution for removing camera shake
S. Harmeling, H. Michael, and B. Schölkopf · 2010
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Generating sharp panoramas from motion-blurred videos
Y. Li, S. B. Kang, N. Joshi, S. M. Seitz, and D. P. Huttenlocher · 2010
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Non-uniform deblurring for shaken images
O. Whyte, J. Sivic, A. Zisserman, and J. Ponce · 2010
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Fast removal of non-uniform camera shake
M. Hirsch, C. J. Schuler, S. Harmeling, and B. Schölkopf · 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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Recording and playback of camera shake: Benchmarking blind deconvolution with a real-world database
R. Köhler, M. Hirsch, B. Mohler, B. Schölkopf, and S. Harmeling · 2012
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Learning to estimate and remove non-uniform image blur
F. Couzinie-Devy, J. Sun, K. Alahari, and J. Ponce · 2013
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Restoring an image taken through a window covered with dirt or rain
D. Eigen, D. Krishnan, and R. Fergus · 2013
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Dynamic scene deblurring
T. H. Kim, B. Ahn, and K. M. Lee · 2013
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Nonlinear camera response functions and image deblurring: Theoretical analysis and practice
Y.-W. Tai, X. Chen, S. Kim, S. J. Kim, F. Li, J. Yang, J. Yu, Y. Matsushita, and M. S. Brown · 2013
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Depth map prediction from a single image using a multi-scale deep network
D. Eigen, C. Puhrsch, and R. Fergus · 2014
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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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Segmentation-free dynamic scene deblurring
T. H. Kim and K. M. Lee · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
Generalized video deblurring for dynamic scenes
T. H. Kim and K. M. Lee · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 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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Learning a convolutional neural network for non-uniform motion blur removal
J. Sun, W. Cao, Z. Xu, and J. Ponce · 2015
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Deep convolutional neural network for image deconvolution
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E. L. Denton, S. Chintala, R. Fergus, et al · 2015
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Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Dynamic scene deblurring using a locally adaptive linear blur model
T. H. Kim, S. Nah, and K. M. Lee · 2016
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A comparative study for single image blind deblurring
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Learning to deblur
C. J. Schuler, M. Hirsch, S. Harmeling, and B. Schölkopf · 2016
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