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 3701–3725 of 7282 papers

TitleStatusHype
DCANet: Dual Convolutional Neural Network with Attention for Image Blind DenoisingCode0
IterativePFN: True Iterative Point Cloud FilteringCode1
Self-Supervised Image Denoising for Real-World Images with Context-aware Transformer—0
Exploration of Lightweight Single Image Denoising with Transformers and Truly Fair TrainingCode1
Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-ResolutionCode1
MM-BSN: Self-Supervised Image Denoising for Real-World with Multi-Mask based on Blind-Spot NetworkCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
Denoising of discrete-time chaotic signals using echo state networks—0
Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver—0
Generative Diffusion Prior for Unified Image Restoration and Enhancement—0
PEACH: Pre-Training Sequence-to-Sequence Multilingual Models for Translation with Semi-Supervised Pseudo-Parallel Document GenerationCode0
ViT-DAE: Transformer-driven Diffusion Autoencoder for Histopathology Image Analysis—0
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models—0
Tunable Convolutions with Parametric Multi-Loss OptimizationCode1
Burstormer: Burst Image Restoration and Enhancement TransformerCode1
ReMoDiffuse: Retrieval-Augmented Motion Diffusion ModelCode2
Spectral Enhanced Rectangle Transformer for Hyperspectral Image DenoisingCode1
Variational Denoising for Variational Quantum Eigensolver—0
FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET DenoisingCode0
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World DenoisingCode1
AMC-Net: An Effective Network for Automatic Modulation Classification—0
-Diff: Infinite Resolution Diffusion with Subsampled Mollified StatesCode1
Diffusion Action SegmentationCode1
Exploiting Multilingualism in Low-resource Neural Machine Translation via Adversarial Learning—0
Unsupervised Anomaly Detection and Localization of Machine Audio: A GAN-based ApproachCode1
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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