Computer Vision
 
Edit

Color Image Denoising

27 papers with code • 61 benchmarks • 8 datasets

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

Datasets

FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising

cszn/FFDNet • • 11 Oct 2017

Due to the fast inference and good performance, discriminative learning methods have been widely studied in image denoising.

441
11 Oct 2017
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.

183
07 Aug 2017
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).

579
11 Apr 2017
Paper
Code

Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification

iorism/CNN • 19 Nov 2016

To address this issue, here we propose a novel feature space deep residual learning algorithm that outperforms the existing residual learning.

46
19 Nov 2016
Paper
Code

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

cszn/DnCNN • • 13 Aug 2016

Discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance.

1,383
13 Aug 2016
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.

20
07 Apr 2016
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
29 Sep 2014
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