Image Denoising Networks ML Frameworks
Deep learning models and implementations for removing noise from images using neural architectures (U-Net, DnCNN, FFDNet, Noise2Void, etc.). Does NOT include traditional signal processing filters, general image restoration, or super-resolution techniques.
There are 42 image denoising networks frameworks tracked. 1 score above 50 (established tier). The highest-rated is CAREamics/careamics at 66/100 with 126 stars and 3,252 monthly downloads.
Get all 42 projects as JSON
curl "https://pt-edge.onrender.com/api/v1/datasets/quality?domain=ml-frameworks&subcategory=image-denoising-networks&limit=20"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
| # | Framework | Score | Tier |
|---|---|---|---|
| 1 |
CAREamics/careamics
A deep-learning library for denoising images using Noise2Void and friends... |
|
Established |
| 2 |
yu4u/noise2noise
An unofficial and partial Keras implementation of "Noise2Noise: Learning... |
|
Emerging |
| 3 |
rgeirhos/texture-vs-shape
Pre-trained models, data, code & materials from the paper "ImageNet-trained... |
|
Emerging |
| 4 |
NICALab/SUPPORT
Accurate denoising of voltage imaging data through statistically unbiased... |
|
Emerging |
| 5 |
cabooster/DeepCAD-RT
DeepCAD-RT: Real-time denoising of fluorescence time-lapse imaging using... |
|
Emerging |
| 6 |
jaewon-lee-b/lte
Local Texture Estimator for Implicit Representation Function, in CVPR 2022 |
|
Emerging |
| 7 |
jiaxi-jiang/FBCNN
Official Code for ICCV 2021 paper "Towards Flexible Blind JPEG Artifacts... |
|
Emerging |
| 8 |
wenbihan/reproducible-image-denoising-state-of-the-art
Collection of popular and reproducible image denoising works. |
|
Emerging |
| 9 |
niuchuangnn/noise2sim
Noise2Sim is a general unsupervised deep denoising method. |
|
Emerging |
| 10 |
tgieruc/Noise2Noise_PyTorch
Unofficial implementation of Noise2Noise (Lehtinen et al., 2018) using PyTorch |
|
Emerging |
| 11 |
ansfl/MEMS-IMU-Denoising
Data-Driven Denoising of Accelerometer Signals |
|
Emerging |
| 12 |
trung-vt/LearningRegularizationParametersForTGV
"Deep unrolling for learning optimal spatially varying regularisation... |
|
Emerging |
| 13 |
ozgurkara99/ISNAS-DIP
ISNAS-DIP: Image Specific Neural Architecture Search for Deep Image Prior [CVPR 2022] |
|
Experimental |
| 14 |
Seattle-Aquarium/underwater-auto-image-encoder
An automated machine learning pipeline that replaces manual image editing... |
|
Experimental |
| 15 |
NikolasMarkou/blind_image_denoising
Implementing CVPR 2020 paper "ROBUST AND INTERPRETABLE BLIND IMAGE DENOISING... |
|
Experimental |
| 16 |
IDKiro/MCT
Multi-Curve Translator for High-Resolution Photorealistic Image Translation |
|
Experimental |
| 17 |
Matin-M/DeepDenoising
Performance and quality evaluation of DCNN based image denoising algorithms |
|
Experimental |
| 18 |
Tombs98/MHNet
A novel network for image reatoration. Mixed Hierarchy Network for Image Restoration. |
|
Experimental |
| 19 |
DeepWave-KAUST/DLDAS_Denoising-pub
Official reproducible material for Noise attenuation in distributed acoustic... |
|
Experimental |
| 20 |
BanmaS/MATLAB-denoise
MathWorks-Excellence-in-Innovation project 193 & SJTU EE397 project |
|
Experimental |
| 21 |
liv-group/reproducible-video-denoising-state-of-the-art
Collection of popular and reproducible video denoising works. |
|
Experimental |
| 22 |
kimbielby/Image-Denoising
Deep learning image denoiser using U-Net. Achieved 33.95 dB PSNR with... |
|
Experimental |
| 23 |
SayantanDutta95/DIVA
Deep Denoising by Quantum Interactive Patches. A deep neural network called... |
|
Experimental |
| 24 |
Omar98165/Noise-Injection-Techniques
🔍 Enhance model robustness with noise injection techniques to tackle messy,... |
|
Experimental |
| 25 |
YasinRezvani/Image_Denoising_Using_FFT_and_DnCNN
Image denoising using both traditional FFT-based filtering and a deep... |
|
Experimental |
| 26 |
Jzy2017/TACL
TIP 2022 | Twin Adversarial Contrastive Learning for Underwater Image... |
|
Experimental |
| 27 |
anonymous-submission01/medical-shape-disentanglement
Self-supervised Disentanglement in Medical Shapes |
|
Experimental |
| 28 |
nhauber99/degradr
Python library for realistically degrading images. |
|
Experimental |
| 29 |
Shakib-IO/Diminishing_Image_Noise_Using_Deep_Learning
Denoising an image is a classical problem that researchers are trying to... |
|
Experimental |
| 30 |
indranil143/Image_Denoiser
Exploring CNN autoencoder techniques for MNIST image denoising, from basic... |
|
Experimental |
| 31 |
lorenzobloise/transmission_tower_electrical_cable_instance_segmentation
This repository contains the code used to train and test a Mask R-CNN model... |
|
Experimental |
| 32 |
mrtineu/fix-erased-numbers
A U-Net Autoencoder built with PyTorch to reconstruct partially erased MNIST... |
|
Experimental |
| 33 |
alr-internship/self-supervised-depth-denoising
Denoising YCB Objects with a self-supervised deep neural network |
|
Experimental |
| 34 |
ksonod/1D_signal_upsampling_and_denoising
Up-sampling and denoising signals using a deep neural network model |
|
Experimental |
| 35 |
lyhkevin/MT-Net
Multi-scale Transformer Network for Cross-Modality MR Image Synthesis (IEEE TMI) |
|
Experimental |
| 36 |
Filippo-Corti/PrincipiEModelliDellaPercezione
Repository for the project "Denoising with N2V" of the class "Principi e... |
|
Experimental |
| 37 |
atefbouzid/Denoising-Dental-X-ray-Images
Academic Project - This project afforded us a valuable opportunity to delve... |
|
Experimental |
| 38 |
MarkoMilenovic01/EdgePreservingImageDenoisingPytorch
PyTorch implementation of an edge-preserving image denoising network trained... |
|
Experimental |
| 39 |
hellloxiaotian/PSLNet
Perceptive self-supervised learning network for noisy image watermark... |
|
Experimental |
| 40 |
hellloxiaotian/SSNet
A self-supervised network for image denoising and watermark removal (Neural... |
|
Experimental |
| 41 |
LeHibouMT/Image-Processing-AI-ML-Project-E3S
Image Processing with AI. Improve image quality and remove image noise. |
|
Experimental |
| 42 |
shangqigao/DeepIDR
An Introduction of "Deep Image Decomposition and Reconstruction" |
|
Experimental |