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 6601–6625 of 7282 papers

TitleStatusHype
Self-supervised Noise2noise Method Utilizing Corrupted Images with a Modular Network for LDCT DenoisingCode0
An Encoder-Decoder Approach to the Paradigm Cell Filling ProblemCode0
Self-supervised OCT Image Denoising with Slice-to-Slice Registration and ReconstructionCode0
Consistency Models for Scalable and Fast Simulation-Based InferenceCode0
Learning normalized image densities via dual score matchingCode0
Going beyond Compositions, DDPMs Can Produce Zero-Shot InterpolationsCode0
Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise DetectionCode0
Learning of Patch-Based Smooth-Plus-Sparse Models for Image ReconstructionCode0
Learning parametric dictionaries for graph signalsCode0
Diffusion Models as Masked AutoencodersCode0
Deep Retinex Decomposition for Low-Light EnhancementCode0
Learning Pixel-Distribution Prior with Wider Convolution for Image DenoisingCode0
Learning Priors in High-frequency Domain for Inverse Imaging ReconstructionCode0
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging ProblemsCode0
Diffusion Models for Computational Neuroimaging: A SurveyCode0
Neural Nearest Neighbors NetworksCode0
An Automated Pipeline for Few-Shot Bird Call Classification: A Case Study with the Tooth-Billed PigeonCode0
Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving AugmentationCode0
PointDGMamba: Domain Generalization of Point Cloud Classification via Generalized State Space ModelCode0
Alioth: A Machine Learning Based Interference-Aware Performance Monitor for Multi-Tenancy Applications in Public CloudCode0
Learning Robust 3D Representation from CLIP via Dual DenoisingCode0
Neural NILM: Deep Neural Networks Applied to Energy DisaggregationCode0
Rethinking Reconstruction and Denoising in the Dark: New Perspective, General Architecture and BeyondCode0
Neural Residual Diffusion Models for Deep Scalable Vision GenerationCode0
Rethinking the CSC Model for Natural ImagesCode0
Show:102550
← PrevPage 265 of 292Next →
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