SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution

Super-resolution through error energy reduction

R. Gerchberg · 1974

Earlier work this paper cites.

Sensor array processing techniques for super resolution multi-line-fitting and straight edge detection

H. K. Aghajan and T. Kailath · 1993

Earlier work this paper cites.

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

D. Martin, C. Fowlkes, D. Tal, and J. Malik · 2001

Earlier work this paper cites.

Image quality assessment: from error visibility to structural similarity

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli · 2004

Earlier work this paper cites.

Sub-pixel mapping of rural land cover objects from fine spatial resolution satellite sensor imagery using super-resolution pixel-swapping

M. Thornton, P. M. Atkinson, and D. Holland · 2006

Earlier work this paper cites.

Super-resolution from a single image

D. Glasner, S. Bagon, and M. Irani · 2009

Earlier work this paper cites.

Image super-resolution via sparse representation

J. Yang, J. Wright, T. S. Huang, and Y. Ma · 2010

Earlier work this paper cites.

Improved face recognition using super-resolution

E. Bilgazyev, B. Efraty, S. K. Shah, and I. A. Kakadiaris · 2011

Earlier work this paper cites.

Cardiac image super-resolution with global correspondence using multi-atlas patchmatch

W. Shi, J. Caballero, C. Ledig, X. Zhuang, W. Bai, K. Bhatia, A. M. S. M. de Marvao, T. Dawes, D. O’Regan, and D. Rueckert · 2013

Earlier work this paper cites.

Image Super-Resolution Using Deep Convolutional Networks

C. Dong, C. C. Loy, K. He, and X. Tang · 2014

Earlier work this paper cites.

A+: Adjusted anchored neighborhood regression for fast super-resolution

R. Timofte, V. De Smet, and L. Van Gool · 2014

Earlier work this paper cites.

Single image super-resolution from transformed self-exemplars

J.-B. Huang, A. Singh, and N. Ahuja · 2015

Cited alongside, same era.

Batch normalization: Accelerating deep network training by reducing internal covariate shift

S. Ioffe and C. Szegedy · 2015

Cited alongside, same era.

Accurate Image Super-Resolution Using Very Deep Convolutional Networks

J. Kim, J. K. Lee, and K. M. Lee · 2015

Cited alongside, same era.

Deeply-Recursive Convolutional Network for Image Super-Resolution

J. Kim, J. K. Lee, and K. M. Lee · 2015

Cited alongside, same era.

U-net: Convolutional networks for biomedical image segmentation

O. Ronneberger, P. Fischer, and T. Brox · 2015

Cited alongside, same era.

Fast and accurate image upscaling with super-resolution forests

S. Schulter, C. Leistner, and H. Bischof · 2015

Deeply Aggregated Alternating Minimization for Image Restoration

Y. Kim, H. Jung, D. Min, and K. Sohn · 2016

Later among the works it cites.

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi · 2016

Later among the works it cites.

Deep multi-scale convolutional neural network for dynamic scene deblurring

Original

S. Nah, T. H. Kim, and K. M. Lee · 2016

Later among the works it cites.

Deconvolution and checkerboard artifacts

A. Odena, V. Dumoulin, and C. Olah · 2016

Later among the works it cites.

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

W. Shi, J. Caballero, F. Huszar, J. Totz, A. P. Aitken, R. Bishop, D. Rueckert, and Z. Wang · 2016

Later among the works it cites.