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 5101–5125 of 7282 papers

TitleStatusHype
Multi-Contextual Design of Convolutional Neural Network for Steganalysis—0
Empirical robustification of pre-trained classifiers—0
Patch-Based Image Restoration using Expectation Propagation—0
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images—0
Direct Reconstruction of Linear Parametric Images from Dynamic PET Using Nonlocal Deep Image Prior—0
Controllable Confidence-Based Image Denoising—0
Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic ModelCode0
Removal of speckle noises from ultrasound images using five different deep learning networksCode0
Simple GNN Regularisation for 3D Molecular Property Prediction & BeyondCode1
SinIR: Efficient General Image Manipulation with Single Image ReconstructionCode1
Signal processing on simplicial complexes—0
Audio Attacks and Defenses against AED Systems -- A Practical Study—0
Non Gaussian Denoising Diffusion ModelsCode1
Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean ImagesCode1
D2C: Diffusion-Denoising Models for Few-shot Conditional GenerationCode1
Posterior Temperature Optimization in Variational Inference for Inverse Problems—0
Learning the optimal Tikhonov regularizer for inverse problemsCode0
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior—0
Adversarial purification with Score-based generative modelsCode1
Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word AlignmentCode1
Wheelchair automation by a hybrid BCI system using SSVEP and eye blinks—0
Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study—0
Deep Interaction between Masking and Mapping Targets for Single-Channel Speech Enhancement—0
Phase retrieval with physics informed zero-shot learning—0
TED-net: Convolution-free T2T Vision Transformer-based Encoder-decoder Dilation network for Low-dose CT DenoisingCode1
Show:102550
← PrevPage 205 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