Computer Vision
 
Edit

Color Image Denoising

18 papers with code • 47 benchmarks • 8 datasets

This task has no description! Would you like to contribute one?

Datasets

Most implemented papers

Most implemented Social Latest No code

Residual Dense Network for Image Super-Resolution

yulunzhang/RDN • • CVPR 2018

In this paper, we propose a novel residual dense network (RDN) to address this problem in image SR. We fully exploit the hierarchical features from all the convolutional layers.

11
Paper
Code

Restormer: Efficient Transformer for High-Resolution Image Restoration

swz30/restormer • • 18 Nov 2021

Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoration and related tasks.

5
Paper
Code

SwinIR: Image Restoration Using Swin Transformer

jingyunliang/swinir • • 23 Aug 2021

In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection.

4
Paper
Code

Real Image Denoising with Feature Attention

saeed-anwar/RIDNet • • ICCV 2019

Deep convolutional neural networks perform better on images containing spatially invariant noise (synthetic noise); however, their performance is limited on real-noisy photographs and requires multiple stage network modeling.

3
Paper
Code

Pre-Trained Image Processing Transformer

huawei-noah/Pretrained-IPT • • CVPR 2021

To maximally excavate the capability of transformer, we present to utilize the well-known ImageNet benchmark for generating a large amount of corrupted image pairs.

3
Paper
Code

Learning Deep CNN Denoiser Prior for Image Restoration

cszn/ircnn • • CVPR 2017

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).

2
Paper
Code

MemNet: A Persistent Memory Network for Image Restoration

tyshiwo/MemNet • • ICCV 2017

We apply MemNet to three image restoration tasks, i. e., image denosing, super-resolution and JPEG deblocking.

2
Paper
Code

Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning

majedelhelou/BUIFD • • 5 Jul 2019

Blind and universal image denoising consists of using a unique model that denoises images with any level of noise.

2
Paper
Code

RENOIR - A Dataset for Real Low-Light Image Noise Reduction

Aftaab99/DenoisingAutoencoder • • 29 Sep 2014

Image denoising algorithms are evaluated using images corrupted by artificial noise, which may lead to incorrect conclusions about their performances on real noise.

1
Paper
Code

Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies

tum-vision/sublabel_relax • 7 Apr 2016

Convex relaxations of nonconvex multilabel problems have been demonstrated to produce superior (provably optimal or near-optimal) solutions to a variety of classical computer vision problems.

1
Paper
Code
Contact us on: hello@paperswithcode.com . Papers With Code is a free resource with all data licensed under CC-BY-SA.
Terms Data policy Cookies policy