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 1651–1700 of 7282 papers

TitleStatusHype
A Physics-based Noise Formation Model for Extreme Low-light Raw DenoisingCode1
GAN-based Priors for Quantifying UncertaintyCode1
Event Probability Mask (EPM) and Event Denoising Convolutional Neural Network (EDnCNN) for Neuromorphic CamerasCode1
Burst Denoising of Dark ImagesCode1
CycleISP: Real Image Restoration via Improved Data SynthesisCode1
Stochastic Frequency Masking to Improve Super-Resolution and Denoising NetworksCode1
A CNN-Based Blind Denoising Method for Endoscopic ImagesCode1
Learning Enriched Features for Real Image Restoration and EnhancementCode1
W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM MappingCode1
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based PenaltiesCode1
3D Quasi-Recurrent Neural Network for Hyperspectral Image DenoisingCode1
Show, Edit and Tell: A Framework for Editing Image CaptionsCode1
Unsupervised Interpretable Representation Learning for Singing Voice SeparationCode1
Denoising IMU Gyroscopes with Deep Learning for Open-Loop Attitude EstimationCode1
Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging ProblemsCode1
Self-Supervised Poisson-Gaussian DenoisingCode1
Replacing Mobile Camera ISP with a Single Deep Learning ModelCode1
Noise2Inverse: Self-supervised deep convolutional denoising for tomographyCode1
Spatial-Adaptive Network for Single Image DenoisingCode1
Multilingual Denoising Pre-training for Neural Machine TranslationCode1
CNN-based InSAR Denoising and Coherence MetricCode1
A deep network for sinogram and CT image reconstructionCode1
A Differentiable Perceptual Audio Metric Learned from Just Noticeable DifferencesCode1
Implementation of the VBM3D Video Denoising Method and Some VariantsCode1
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial DefenseCode1
Stacked DeBERT: All Attention in Incomplete Data for Text ClassificationCode1
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximationCode1
Scale-wise Convolution for Image RestorationCode1
Fully Trainable and Interpretable Non-Local Sparse Models for Image RestorationCode1
Scientific Image Restoration AnywhereCode1
Penalty Method for Inversion-Free Deep Bilevel OptimizationCode1
Online matrix factorization for Markovian data and applications to Network Dictionary LearningCode1
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and ComprehensionCode1
Learning Energy-Based Models in High-Dimensional Spaces with Multi-scale Denoising Score MatchingCode1
Overcoming Data Limitation in Medical Visual Question AnsweringCode1
Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View SynthesisCode1
Memory-Efficient Hierarchical Neural Architecture Search for Image DenoisingCode1
Unsupervised Sketch-to-Photo SynthesisCode1
Denoising Auto-encoding Priors in Undecimated Wavelet Domain for MR Image ReconstructionCode1
Variational Denoising Network: Toward Blind Noise Modeling and RemovalCode1
Backpropagation-Friendly EigendecompositionCode1
Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted ImageCode1
A Bayesian Model of Dose-Response for Cancer Drug StudiesCode1
Probabilistic Noise2Void: Unsupervised Content-Aware DenoisingCode1
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise ModelingCode1
Learning Deformable Kernels for Image and Video DenoisingCode1
TomoGAN: Low-Dose Synchrotron X-Ray Tomography with Generative Adversarial NetworksCode1
Extending Stein's unbiased risk estimator to train deep denoisers with correlated pairs of noisy imagesCode1
Noise2Self: Blind Denoising by Self-SupervisionCode1
A Poisson-Gaussian Denoising Dataset with Real Fluorescence Microscopy ImagesCode1
Show:102550
← PrevPage 34 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