SOTAVerified

Denoising

Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.

( Image credit: Beyond a Gaussian Denoiser )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5251–5300 of 7282 papers

TitleStatusHype
Clean or Annotate: How to Spend a Limited Data Collection Budget—0
Hyperspectral Image Mixed Noise Removal Using Subspace Representation and Deep CNN Image PriorCode0
Spark Deficient Gabor Frames for Inverse Problems—0
Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Framework—0
Denoising Diffusion Gamma Models—0
Fetal Gender Identification using Machine and Deep Learning Algorithms on Phonocardiogram Signals—0
Game Theory for Adversarial Attacks and DefensesCode0
Graphs as Tools to Improve Deep Learning Methods—0
Accelerated First Order Methods for Variational ImagingCode0
TSN-CA: A Two-Stage Network with Channel Attention for Low-Light Image Enhancement—0
Detection of blue whale vocalisations using a temporal-domain convolutional neural network—0
Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation—0
A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood FiltersCode0
Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration—0
Generative Pseudo-Inverse Memory—0
Optimizing Few-Step Diffusion Samplers by Gradient Descent—0
Dictionary Learning Under Generative Coefficient Priors with Applications to Compression—0
A noise reduction method for force measurements in water entry experiments based on the Ensemble Empirical Mode Decomposition—0
A General Unified Graph Neural Network Framework Against Adversarial Attacks—0
Robust Learning with Adaptive Sample Credibility Modeling—0
Training Data Size Induced Double Descent For Denoising Neural Networks and the Role of Training Noise Level—0
Stabilized Likelihood-based Imitation Learning via Denoising Continuous Normalizing Flow—0
Learning From Unpaired Data: A Variational Bayes Approach—0
Noise Reconstruction and Removal Network: A New Way to Denoise FIB-SEM Images—0
Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning—0
GenTAL: Generative Denoising Skip-gram Transformer for Unsupervised Binary Code Similarity Detection—0
Embedding models through the lens of Stable Coloring—0
Automated Channel Pruning with Learned Importance—0
Cross-Domain Lossy Compression as Optimal Transport with an Entropy Bottleneck—0
Neural Knitworks: Patched Neural Implicit Representation Networks—0
Self-supervised regression learning using domain knowledge: Applications to improving self-supervised image denoising—0
Hyperparameter selection for Discrete Mumford-ShahCode0
Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation—0
ECG Beat Representation and Delineation by means of Variable Projection—0
Gotta Go Fast with Score-Based Generative Models—0
DemiNet: Dependency-Aware Multi-Interest Network with Self-Supervised Graph Learning for Click-Through Rate Prediction—0
Learning-based Noise Component Map Estimation for Image Denoising—0
Untrained Graph Neural Networks for DenoisingCode0
Nonlinear Denoising, Linear Demixing—0
Joint Optical Neuroimaging Denoising with Semantic Tasks—0
From Simulated to Visual Data: A Robust Low-Rank Tensor Completion Approach using lp-Regression for Outlier Resistance—0
Network Refinement: A unified framework for enhancing signal or removing noise of networks—0
Removing Noise from Extracellular Neural Recordings Using Fully Convolutional Denoising AutoencodersCode0
DyLex: Incorporating Dynamic Lexicons into BERT for Sequence LabelingCode0
SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising—0
Denoising Large-Scale Image Captioning from Alt-text Data using Content Selection Models—0
Improving Reproducibility and Performance of Radiomics in Low Dose CT using Cycle GANs—0
Eformer: Edge Enhancement based Transformer for Medical Image Denoising—0
Image Deraining and Denoising Convolutional Neural Network ForAutonomous Driving—0
Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis—0
Show:102550
← PrevPage 106 of 146Next →
All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified