About

Image Restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image. Corruption may occur due to the image-capture process (e.g., noise, lens blur), post-processing (e.g., JPEG compression), or photography in non-ideal conditions (e.g., haze, motion blur).

Source: Blind Image Restoration without Prior Knowledge

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Greatest papers with code

Old Photo Restoration via Deep Latent Space Translation

14 Sep 2020microsoft/Bringing-Old-Photos-Back-to-Life

Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize.

IMAGE RESTORATION

Bringing Old Photos Back to Life

CVPR 2020 microsoft/Bringing-Old-Photos-Back-to-Life

Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize.

IMAGE RESTORATION

Deep Image Prior

CVPR 2018 DmitryUlyanov/deep-image-prior

In this paper, we show that, on the contrary, the structure of a generator network is sufficient to capture a great deal of low-level image statistics prior to any learning.

IMAGE DENOISING IMAGE INPAINTING IMAGE RESTORATION JPEG COMPRESSION ARTIFACT REDUCTION SUPER-RESOLUTION

Noise2Noise: Learning Image Restoration without Clean Data

ICML 2018 NVlabs/noise2noise

We apply basic statistical reasoning to signal reconstruction by machine learning -- learning to map corrupted observations to clean signals -- with a simple and powerful conclusion: it is possible to learn to restore images by only looking at corrupted examples, at performance at and sometimes exceeding training using clean data, without explicit image priors or likelihood models of the corruption.

IMAGE RESTORATION SALT-AND-PEPPER NOISE REMOVAL

Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels

CVPR 2019 cszn/DPSR

In this paper, we propose a principled formulation and framework by extending bicubic degradation based deep SISR with the help of plug-and-play framework to handle LR images with arbitrary blur kernels.

DEBLURRING IMAGE RESTORATION IMAGE SUPER-RESOLUTION

Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections

29 Jun 2016titu1994/Image-Super-Resolution

In this work, we propose a very deep fully convolutional auto-encoder network for image restoration, which is a encoding-decoding framework with symmetric convolutional-deconvolutional layers.

IMAGE DENOISING IMAGE RESTORATION SUPER-RESOLUTION

DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better

ICCV 2019 kritiksoman/GIMP-ML

We present a new end-to-end generative adversarial network (GAN) for single image motion deblurring, named DeblurGAN-v2, which considerably boosts state-of-the-art deblurring efficiency, quality, and flexibility.

Ranked #14 on Deblurring on GoPro (using extra training data)

IMAGE RESTORATION SINGLE-IMAGE BLIND DEBLURRING

EnlightenGAN: Deep Light Enhancement without Paired Supervision

17 Jun 2019kritiksoman/GIMP-ML

Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data?

IMAGE RESTORATION LOW-LIGHT IMAGE ENHANCEMENT

Learning Deep CNN Denoiser Prior for Image Restoration

CVPR 2017 cszn/ircnn

Recent works have revealed that, with the aid of variable splitting techniques, denoiser prior can be plugged in as a modular part of model-based optimization methods to solve other inverse problems (e. g., deblurring).

COLOR IMAGE DENOISING DEBLURRING IMAGE DENOISING IMAGE RESTORATION

The 2018 PIRM Challenge on Perceptual Image Super-resolution

20 Sep 2018alterzero/DBPN-Pytorch

This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at ECCV 2018.

IMAGE RESTORATION IMAGE SUPER-RESOLUTION