Grayscale Image Denoising

6 papers with code • 39 benchmarks • 3 datasets

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Most implemented papers

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.

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.

Index Network

poppinace/indexnet_matting 11 Aug 2019

By viewing the indices as a function of the feature map, we introduce the concept of "learning to index", and present a novel index-guided encoder-decoder framework where indices are self-learned adaptively from data and are used to guide the downsampling and upsampling stages, without extra training supervision.

LIDIA: Lightweight Learned Image Denoising with Instance Adaptation

grishavak/LIDIA-denoiser 17 Nov 2019

This work proposes a novel lightweight learnable architecture for image denoising, and presents a combination of supervised and unsupervised training of it, the first aiming for a universal denoiser and the second for adapting it to the incoming image.

CDLNet: Robust and Interpretable Denoising Through Deep Convolutional Dictionary Learning

nikopj/cdlnet-ojsp 5 Mar 2021

In addition, we leverage the model's interpretable construction to propose an augmentation of the network's thresholds that enables state-of-the-art blind denoising performance and near-perfect generalization on noise-levels unseen during training.

Adversarial Distortion Learning for Medical Image Denoising

mogvision/adl 29 Apr 2022

The proposed ADL consists of two auto-encoders: a denoiser and a discriminator.