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 1651–1675 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
Show:102550
← PrevPage 67 of 292Next →
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