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 1401–1450 of 7282 papers

TitleStatusHype
An Analysis and Implementation of the HDR+ Burst Denoising MethodCode1
MAAD: A Model and Dataset for "Attended Awareness" in DrivingCode1
Toward Degradation-Robust Voice ConversionCode1
Rethinking Noise Synthesis and Modeling in Raw DenoisingCode1
Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising LearningCode1
Score-based diffusion models for accelerated MRICode1
Burst Image Restoration and EnhancementCode1
On audio enhancement via online non-negative matrix factorizationCode1
Generative Modeling with Optimal Transport MapsCode1
Adaptive Unfolding Total Variation Network for Low-Light Image EnhancementCode1
Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised LearningCode1
BARTpho: Pre-trained Sequence-to-Sequence Models for VietnameseCode1
Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-LabelingCode1
FastHyMix: Fast and Parameter-free Hyperspectral Image Mixed Noise RemovalCode1
WINNet: Wavelet-inspired Invertible Network for Image DenoisingCode1
Dynamic Attentive Graph Learning for Image RestorationCode1
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and GenerationCode1
Rethinking Zero-shot Neural Machine Translation: From a Perspective of Latent VariablesCode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
Sentence Bottleneck Autoencoders from Transformer Language ModelsCode1
Rethinking Deep Image Prior for DenoisingCode1
Self-supervised Neural Networks for Spectral Snapshot Compressive ImagingCode1
Machine learning on DNA-encoded library count data using an uncertainty-aware probabilistic loss functionCode1
Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text SummarizationCode1
DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT DenoisingCode1
Noise2Fast: Fast Self-Supervised Single Image Blind DenoisingCode1
Deep Reparametrization of Multi-Frame Super-Resolution and DenoisingCode1
Thermal Image Processing via Physics-Inspired Deep NetworksCode1
spectrai: A deep learning framework for spectral dataCode1
ILVR: Conditioning Method for Denoising Diffusion Probabilistic ModelsCode1
Optimal Transport for Unsupervised Denoising LearningCode1
Physics-based Noise Modeling for Extreme Low-light PhotographyCode1
Toward Spatially Unbiased Generative ModelsCode1
CERL: A Unified Optimization Framework for Light Enhancement with Realistic NoiseCode1
DCT2net: an interpretable shallow CNN for image denoisingCode1
Score-Based Point Cloud DenoisingCode1
Wavelet Transform-assisted Adaptive Generative Modeling for ColorizationCode1
On Measuring and Controlling the Spectral Bias of the Deep Image PriorCode1
Deep Mesh Prior: Unsupervised Mesh Restoration using Graph Convolutional NetworksCode1
DAEMA: Denoising Autoencoder with Mask AttentionCode1
Uncertainty-Guided Progressive GANs for Medical Image TranslationCode1
R2RNet: Low-light Image Enhancement via Real-low to Real-normal NetworkCode1
Progressive Joint Low-light Enhancement and Noise Removal for Raw ImagesCode1
Fast Monte Carlo Rendering via Multi-Resolution SamplingCode1
Deformed2Self: Self-Supervised Denoising for Dynamic Medical ImagingCode1
Deep Convolutional Dictionary Learning for Image DenoisingCode1
Adaptive Consistency Prior Based Deep Network for Image DenoisingCode1
Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image DenoisingCode1
Effective Snapshot Compressive-Spectral Imaging via Deep Denoising and Total Variation PriorsCode1
End-to-End Learning for Joint Image Demosaicing, Denoising and Super-ResolutionCode1
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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