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 1501–1525 of 7282 papers

TitleStatusHype
Multi-Stage Raw Video Denoising with Adversarial Loss and Gradient MaskCode1
Self-supervised Low Light Image Enhancement and DenoisingCode1
Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-CaseCode1
Uncertainty-aware Generalized Adaptive CycleGANCode1
Denoising Higher-order Moments for Blind Digital Modulation Identification in Multiple-antenna SystemsCode1
ISCL: Interdependent Self-Cooperative Learning for Unpaired Image DenoisingCode1
Joint self-supervised blind denoising and noise estimationCode1
Intermediate Layer Optimization for Inverse Problems using Deep Generative ModelsCode1
How Framelets Enhance Graph Neural NetworksCode1
Learning low-rank latent mesoscale structures in networksCode1
Input Similarity from the Neural Network PerspectiveCode1
Argmax Flows and Multinomial Diffusion: Learning Categorical DistributionsCode1
Deep learning architectural designs for super-resolution of noisy imagesCode1
Real-time Denoising and Dereverberation with Tiny Recurrent U-NetCode1
Multi-Stage Progressive Image RestorationCode1
Model-based multi-parameter mappingCode1
Civil Rephrases Of Toxic Texts With Self-Supervised TransformersCode1
Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video DenoisingCode1
Joint Denoising and Demosaicking with Green Channel Prior for Real-world Burst ImagesCode1
Deep Universal Blind Image DenoisingCode1
Plug-and-Play Algorithms for Video Snapshot Compressive ImagingCode1
DENet: a deep architecture for audio surveillance applicationsCode1
Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy ImagesCode1
Hyperspectral image denoising based on global and non-local low-rank factorizationsCode1
Knowledge Distillation in Iterative Generative Models for Improved Sampling SpeedCode1
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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