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 6176–6200 of 7282 papers

TitleStatusHype
Speech Audio Generation from dynamic MRI via a Knowledge Enhanced Conditional Variational Autoencoder—0
Denoising Adversarial Autoencoders: Classifying Skin Lesions Using Limited Labelled Training Data—0
Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels—0
Denoising and Adaptive Online Vertical Federated Learning for Sequential Multi-Sensor Data in Industrial Internet of Things—0
Denoising and Alignment: Rethinking Domain Generalization for Multimodal Face Anti-Spoofing—0
Denoising and Completion of 3D Data via Multidimensional Dictionary Learning—0
Denoising and compression in wavelet domain via projection onto approximation coefficients—0
Denoising and Covariance Estimation of Single Particle Cryo-EM Images—0
Denoising and feature extraction in photoemission spectra with variational auto-encoder neural networks—0
Denoising and Optical and SAR Image Classifications Based on Feature Extraction and Sparse Representation—0
Speech denoising by parametric resynthesis—0
Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir Computing—0
Denoising and Segmentation of Epigraphical Scripts—0
Denoising and Selecting Pseudo-Heatmaps for Semi-Supervised Human Pose Estimation—0
Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning—0
Denoising Arterial Spin Labeling Cerebral Blood Flow Images Using Deep Learning—0
Denoising Atmospheric Temperature Measurements Taken by the Mars Science Laboratory on the Martian Surface—0
Denoising Attention for Query-aware User Modeling in Personalized Search—0
Denoising Autoencoder-based Defensive Distillation as an Adversarial Robustness Algorithm—0
Denoising Autoencoders for Overgeneralization in Neural Networks—0
Denoising Auto-encoder with Recurrent Skip Connections and Residual Regression for Music Source Separation—0
AATCT-IDS: A Benchmark Abdominal Adipose Tissue CT Image Dataset for Image Denoising, Semantic Segmentation, and Radiomics Evaluation—0
Denoising Autoregressive Representation Learning—0
Vehicular Visible Light Communications Noise Analysis and Autoencoder Based Denoising—0
Denoising-based image reconstruction from pixels located at non-integer positions—0
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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