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

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Showing 726–750 of 7282 papers

TitleStatusHype
Ship in Sight: Diffusion Models for Ship-Image Super ResolutionCode1
DiffStyler: Diffusion-based Localized Image Style TransferCode1
Noise2Noise Denoising of CRISM Hyperspectral DataCode1
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image ReconstructionCode1
FusionINN: Decomposable Image Fusion for Brain Tumor MonitoringCode1
Denoising Diffusion Models for 3D Healthy Brain Tissue InpaintingCode1
Generalized Consistency Trajectory Models for Image ManipulationCode1
VQ-NeRV: A Vector Quantized Neural Representation for VideosCode1
Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly DetectionCode1
WIA-LD2ND: Wavelet-based Image Alignment for Self-supervised Low-Dose CT DenoisingCode1
Divide-and-Conquer Posterior Sampling for Denoising Diffusion PriorsCode1
Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
MD-Dose: A diffusion model based on the Mamba for radiation dose predictionCode1
eDifFIQA: Towards Efficient Face Image Quality Assessment Based On Denoising Diffusion Probabilistic ModelsCode1
Low-dose CT Denoising with Language-engaged Dual-space AlignmentCode1
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Privacy-Preserving Diffusion Model Using Homomorphic EncryptionCode1
DiffSF: Diffusion Models for Scene Flow EstimationCode1
SSDRec: Self-Augmented Sequence Denoising for Sequential RecommendationCode1
On the Asymptotic Mean Square Error Optimality of Diffusion ModelsCode1
TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model EncodingsCode1
Listening to the Noise: Blind Denoising with Gibbs DiffusionCode1
Purified and Unified Steganographic NetworkCode1
Label-Noise Robust Diffusion ModelsCode1
Diffusion Posterior Proximal Sampling for Image RestorationCode1
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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