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 5426–5450 of 7282 papers

TitleStatusHype
Hyperspectral Image Denoising with Log-Based Robust PCA—0
Distantly-Supervised Long-Tailed Relation Extraction Using Constraint GraphsCode0
Real-time Human Action Recognition Using Locally Aggregated Kinematic-Guided Skeletonlet and Supervised Hashing-by-Analysis Model—0
SSCAN: A Spatial-spectral Cross Attention Network for Hyperspectral Image Denoising—0
Denoising Noisy Neural Networks: A Bayesian Approach with CompensationCode0
Multi-Perspective Anomaly Detection—0
Learning Robust Recommenders through Cross-Model Agreement—0
Graph Sanitation with Application to Node Classification—0
End-to-End Unsupervised Document Image Blind Denoising—0
MIEHDR CNN: Main Image Enhancement based Ghost-Free High Dynamic Range Imaging using Dual-Lens Systems—0
Overparametrization of HyperNetworks at Fixed FLOP-Count Enables Fast Neural Image Enhancement—0
A Fusion-Denoising Attack on InstaHide with Data AugmentationCode0
GCN-MIF: Graph Convolutional Network with Multi-Information Fusion for Low-dose CT DenoisingCode0
Spelling Correction with Denoising Transformer—0
Poisoning MorphNet for Clean-Label Backdoor Attack to Point Clouds—0
EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models—0
Optimal Receive Beamforming for Over-the-Air Computation—0
Graph Feature Gating Networks—0
Zero-Shot Personalized Speech Enhancement through Speaker-Informed Model Selection—0
Test-Time Adaptation Toward Personalized Speech Enhancement: Zero-Shot Learning with Knowledge Distillation—0
LINN: Lifting Inspired Invertible Neural Network for Image DenoisingCode0
Real-Time Video Super-Resolution by Joint Local Inference and Global Parameter Estimation—0
Towards Interpretable and Transferable Speech Emotion Recognition: Latent Representation Based Analysis of Features, Methods and Corpora—0
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series—0
Blind microscopy image denoising with a deep residual and multiscale encoder/decoder networkCode0
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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