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 22512275 of 7282 papers

TitleStatusHype
LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation LearningCode0
AGConv: Adaptive Graph Convolution on 3D Point CloudsCode0
Interspeech 2021 Deep Noise Suppression ChallengeCode0
Invariant Risk Minimization Is A Total Variation ModelCode0
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace NormCode0
Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal BoundsCode0
Active Generation for Image ClassificationCode0
Cross-Domain Conditional Diffusion Models for Time Series ImputationCode0
Assessing The Impact of CNN Auto Encoder-Based Image Denoising on Image Classification TasksCode0
Interacting Diffusion Processes for Event Sequence ForecastingCode0
Instance Regularization for Discriminative Language Model Pre-trainingCode0
A Fusion-Denoising Attack on InstaHide with Data AugmentationCode0
Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion ModelCode0
Inter-Beat Interval Estimation with Tiramisu Model: A Novel Approach with Reduced ErrorCode0
Inferring Neural Signed Distance Functions by Overfitting on Single Noisy Point Clouds through Finetuning Data-Driven based PriorsCode0
Credit Card Fraud Detection Using Autoencoder Neural NetworkCode0
Inference-Time Diffusion Model DistillationCode0
Inference Stage Denoising for Undersampled MRI ReconstructionCode0
Index NetworkCode0
Inexact Derivative-Free Optimization for Bilevel LearningCode0
Informed Graph Learning By Domain Knowledge Injection and Smooth Graph Signal RepresentationCode0
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal DenoisingCode0
Coupled Dictionary Learning for Multi-contrast MRI ReconstructionCode0
Improving Social Meaning Detection with Pragmatic Masking and Surrogate Fine-TuningCode0
A Simple Yet Effective SVD-GCN for Directed GraphsCode0
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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