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 4551–4575 of 7282 papers

TitleStatusHype
RoBLEURT Submission for the WMT2021 Metrics Task—0
Low-rank Meets Sparseness: An Integrated Spatial-Spectral Total Variation Approach to Hyperspectral Denoising—0
A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image DenoisingCode0
Self-supervision versus synthetic datasets: which is the lesser evil in the context of video denoising?—0
Joint-Modal Label Denoising for Weakly-Supervised Audio-Visual Video ParsingCode1
Signal Recovery with Non-Expansive Generative Network Priors—0
Less is More: Reweighting Important Spectral Graph Features for RecommendationCode1
Improved far-field speech recognition using Joint Variational Autoencoder—0
Gabor is Enough: Interpretable Deep Denoising with a Gabor Synthesis Dictionary PriorCode1
Capturing the Denoising Effect of PCA via Compression Ratio—0
A Mask-Based Adversarial Defense Scheme—0
Denoising of Three-Dimensional Fast Spin Echo Magnetic Resonance Images of Knee Joints using Spatial-Variant Noise-Relevant Residual Learning of Convolution Neural Network—0
Learn from Unpaired Data for Image Restoration: A Variational Bayes ApproachCode1
Parametric Level-sets Enhanced To Improve Reconstruction (PaLEnTIR)—0
FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech SynthesisCode2
Self-supervised Learning for Sonar Image ClassificationCode1
Learning Enriched Features for Fast Image Restoration and Enhancement—0
Speech Dereverberation with A Reverberation Time Shortening Target—0
DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations—0
Partial Relaxed Optimal Transport for Denoised Recommendation—0
A qualitative investigation of optical flow algorithms for video denoising—0
Shallow camera pipeline for night photography rendering—0
Dynamic Point Cloud Denoising via Gradient Fields—0
Fast Multi-grid Methods for Minimizing Curvature EnergyCode0
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising PackageCode1
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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