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

Showing 22262250 of 7282 papers

TitleStatusHype
A Generative Adversarial Approach To ECG Synthesis And DenoisingCode0
Iterative Residual CNNs for Burst Photography ApplicationsCode0
A survey of probabilistic generative frameworks for molecular simulationsCode0
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Invertible generative models for inverse problems: mitigating representation error and dataset biasCode0
Invertible Kernel PCA with Random Fourier FeaturesCode0
Investigating the effect of residual and highway connections in speech enhancement modelsCode0
Isotropic and Steerable Wavelets in N Dimensions. A multiresolution analysis framework for ITKCode0
Iterative Joint Image Demosaicking and Denoising using a Residual Denoising NetworkCode0
A Structure-Guided Diffusion Model for Large-Hole Image CompletionCode0
Invariant Risk Minimization Is A Total Variation ModelCode0
Cryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy DataCode0
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace NormCode0
Interspeech 2021 Deep Noise Suppression ChallengeCode0
Interacting Diffusion Processes for Event Sequence ForecastingCode0
Inter-Beat Interval Estimation with Tiramisu Model: A Novel Approach with Reduced ErrorCode0
Instance Regularization for Discriminative Language Model Pre-trainingCode0
Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion ModelCode0
AGEM: Solving Linear Inverse Problems via Deep Priors and SamplingCode0
Labeling, Cutting, Grouping: an Efficient Text Line Segmentation Method for Medieval ManuscriptsCode0
Inference-Time Diffusion Model DistillationCode0
Inexact Derivative-Free Optimization for Bilevel LearningCode0
AGConv: Adaptive Graph Convolution on 3D Point CloudsCode0
Inference Stage Denoising for Undersampled MRI ReconstructionCode0
Index NetworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified