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

Benchmarks

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Subtasks

Datasets

Latest papers with code

Plug-and-Play external and internal priors for image restoration

15 Feb 2021sedaboni/PnP-TV

We propose a new PnP scheme, based on the Half-Quadratic Splitting proximal algorithm, combining external and internal priors.

IMAGE RESTORATION

0
15 Feb 2021

Multi-Stage Progressive Image Restoration

4 Feb 2021swz30/MPRNet

At each stage, we introduce a novel per-pixel adaptive design that leverages in-situ supervised attention to reweight the local features.

DEBLURRING IMAGE DENOISING IMAGE RESTORATION SINGLE IMAGE DERAINING

48
04 Feb 2021

GAN Inversion: A Survey

14 Jan 2021weihaox/documents

GAN inversion aims to invert a given image back into the latent space of a pretrained GAN model, for the image to be faithfully reconstructed from the inverted code by the generator.

IMAGE MANIPULATION IMAGE RESTORATION

1
14 Jan 2021

LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CT

13 Dec 2020maybe198376/LEARN-Plus-Plus

Compressed sensing (CS) computed tomography has been proven to be important for several clinical applications, such as sparse-view computed tomography (CT), digital tomosynthesis and interior tomography.

COMPUTED TOMOGRAPHY (CT) IMAGE RESTORATION

1
13 Dec 2020

Bayesian Image Reconstruction using Deep Generative Models

8 Dec 2020razvanmarinescu/brgm

Machine learning models are commonly trained end-to-end and in a supervised setting, using paired (input, output) data.

IMAGE DENOISING IMAGE INPAINTING IMAGE RECONSTRUCTION IMAGE RESTORATION IMAGE SUPER-RESOLUTION

14
08 Dec 2020

Color Image Restoration Exploiting Inter-channel Correlation with a 3-stage CNN

8 Dec 2020amnesiack/CNNCDM3CIR

We demonstrate the capabilities of the proposed 3-stage structure with three typical color image restoration tasks: color image demosaicking, color compression artifacts reduction, and real-world color image denoising.

COLOR IMAGE DENOISING DEMOSAICKING IMAGE DENOISING IMAGE RECONSTRUCTION

1
08 Dec 2020

CLEARER: Multi-Scale Neural Architecture Search for Image Restoration

NeurIPS 2020 XLearning-SCU/2020-NeurIPS-CLEARER

Different from the existing labor-intensive handcrafted architecture design paradigms, we present a novel method, termed as multi-sCaLe nEural ARchitecture sEarch for image Restoration (CLEARER), which is a specifically designed neural architecture search (NAS) for image restoration.

IMAGE DENOISING IMAGE RESTORATION NEURAL ARCHITECTURE SEARCH RAIN REMOVAL

5
01 Dec 2020

Navigating the GAN Parameter Space for Semantic Image Editing

27 Nov 2020yandex-research/navigan

In contrast to existing works, which mostly operate by latent codes, we discover interpretable directions in the space of the generator parameters.

IMAGE RESTORATION IMAGE-TO-IMAGE TRANSLATION

217
27 Nov 2020

Rank-One Network: An Effective Framework for Image Restoration

25 Nov 2020shangqigao/RONet

The RO decomposition is developed to decompose a corrupted image into the RO components and residual.

COLOR IMAGE DENOISING IMAGE DENOISING IMAGE RESTORATION IMAGE SUPER-RESOLUTION

9
25 Nov 2020

Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media with Airlight and Scattering Coefficient Estimation

18 Nov 2020yfujimura/DCV-release

We also propose a method of estimating scattering parameters, such as airlight, and a scattering coefficient, which are required for our dehazing cost volume.

3D RECONSTRUCTION DEPTH ESTIMATION IMAGE RESTORATION STRUCTURE FROM MOTION

2
18 Nov 2020