Blind Image Restoration with Flow Based Priors

Nonlinear total variation based noise removal algorithms

Rudin, L. I., Osher, S., and Fatemi, E · 1992

Earlier work this paper cites.

Gradient-based learning applied to document recognition

LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P · 1998

Earlier work this paper cites.

Removing camera shake from a single photograph

Fergus, R., Singh, B., Hertzmann, A., Roweis, S. T., and Freeman, W. T · 2006

Earlier work this paper cites.

Image super-resolution using very deep residual channel attention networks

Zhang, Y., Li, K., Li, K., Wang, L., Zhong, B., and Fu, Y · 2009

Earlier work this paper cites.

Single image haze removal using dark channel prior

He, K., Sun, J., and Tang, X · 2010

Earlier work this paper cites.

NICE: non-linear independent components estimation

Original

Dinh, L., Krueger, D., and Bengio, Y · 2015

Earlier work this paper cites.

Adam: A method for stochastic optimization

Original

Kingma, D. P. and Ba, J · 2015

Earlier work this paper cites.

Variational inference with normalizing flows

Rezende, D. J. and Mohamed, S · 2015

Earlier work this paper cites.

Deep residual learning for image recognition

He, K., Zhang, X., Ren, S., and Sun, J · 2016

Earlier work this paper cites.

Context encoders: Feature learning by inpainting

Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., and Efros, A. A · 2016

Cited alongside, same era.

NTIRE 2017 challenge on single image super-resolution: Dataset and study

Agustsson, E. and Timofte, R · 2017

Cited alongside, same era.

Deep mean-shift priors for image restoration

Bigdeli, S. A., Zwicker, M., Favaro, P., and Jin, M · 2017

Cited alongside, same era.

Density estimation using real NVP

Dinh, L., Sohl-Dickstein, J., and Bengio, S · 2017

Cited alongside, same era.

Learning proximal operators: Using denoising networks for regularizing inverse imaging problems

Meinhardt, T., Moller, M., Hazirbas, C., and Cremers, D · 2017

Cited alongside, same era.

Joint estimation of camera pose, depth, deblurring, and super-resolution from a blurred image sequence

Park, H. and Mu Lee, K · 2017

Deep image prior

Ulyanov, D., Vedaldi, A., and Lempitsky, V · 2018

Later among the works it cites.

A fully progressive approach to single-image super-resolution

Wang, Y., Perazzi, F., McWilliams, B., Sorkine-Hornung, A., Sorkine-Hornung, O., and Schroers, C · 2018

Later among the works it cites.

Blind super-resolution kernel estimation using an internal-gan

Bell-Kligler, S., Shocher, A., and Irani, M · 2019

Later among the works it cites.

A bayesian perspective on the deep image prior

Cheng, Z., Gadelha, M., Maji, S., and Sheldon, D · 2019

Later among the works it cites.

Blind image super resolution with spatially variant degradations

Cornillère, V., Djelouah, A., Yifan, W., Sorkine-Hornung, O., and Schroers, C · 2019

Later among the works it cites.

Deepred: Deep image prior powered by red

Mataev, G., Milanfar, P., and Elad, M · 2019

Later among the works it cites.