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 2201–2225 of 7282 papers

TitleStatusHype
DANAE: a denoising autoencoder for underwater attitude estimationCode0
DALI: Domain Adaptive LiDAR Object Detection via Distribution-level and Instance-level Pseudo Label DenoisingCode0
A Theoretically Guaranteed Quaternion Weighted Schatten p-norm Minimization Method for Color Image RestorationCode0
Joint Adaptive Sparsity and Low-Rankness on the Fly: An Online Tensor Reconstruction Scheme for Video DenoisingCode0
Joint Demosaicking and Denoising by Fine-Tuning of Bursts of Raw ImagesCode0
Iterative Residual CNNs for Burst Photography ApplicationsCode0
Iterative Joint Image Demosaicking and Denoising using a Residual Denoising NetworkCode0
Iterative Learning for Joint Image Denoising and Motion Artifact Correction of 3D Brain MRICode0
Iterative PET Image Reconstruction Using Convolutional Neural Network RepresentationCode0
D2-Net: Weakly-Supervised Action Localization via Discriminative Embeddings and Denoised ActivationsCode0
Iterative Camera-LiDAR Extrinsic Optimization via Surrogate DiffusionCode0
D2Diff : A Dual Domain Diffusion Model for Accurate Multi-Contrast MRI SynthesisCode0
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Investigating the effect of residual and highway connections in speech enhancement modelsCode0
Cycle Consistent Adversarial Denoising Network for Multiphase Coronary CT AngiographyCode0
Invertible generative models for inverse problems: mitigating representation error and dataset biasCode0
A Bayesian Perspective on the Deep Image PriorCode0
Invertible Kernel PCA with Random Fourier FeaturesCode0
Isotropic and Steerable Wavelets in N Dimensions. A multiresolution analysis framework for ITKCode0
Joint Enhancement and Denoising Method via Sequential DecompositionCode0
CurvPnP: Plug-and-play Blind Image Restoration with Deep Curvature DenoiserCode0
CUR Transformer: A Convolutional Unbiased Regional Transformer for Image DenoisingCode0
A Generative Adversarial Approach To ECG Synthesis And DenoisingCode0
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace NormCode0
Interspeech 2021 Deep Noise Suppression ChallengeCode0
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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