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 3826–3850 of 7282 papers

TitleStatusHype
mDAE : modified Denoising AutoEncoder for missing data imputation—0
MDPose: Human Skeletal Motion Reconstruction Using WiFi Micro-Doppler Signatures—0
MD-ProjTex: Texturing 3D Shapes with Multi-Diffusion Projection—0
MDSGen: Fast and Efficient Masked Diffusion Temporal-Aware Transformers for Open-Domain Sound Generation—0
Towards High-quality HDR Deghosting with Conditional Diffusion Models—0
Fast And Efficient Boolean Matrix Factorization By Geometric Segmentation—0
Towards Interpretable and Transferable Speech Emotion Recognition: Latent Representation Based Analysis of Features, Methods and Corpora—0
MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applications—0
MedDiff: Generating Electronic Health Records using Accelerated Denoising Diffusion Model—0
MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI—0
MedGAN: Medical Image Translation using GANs—0
Med-gte-hybrid: A contextual embedding transformer model for extracting actionable information from clinical texts—0
Adaptive Pixel-wise Structured Sparse Network for Efficient CNNs—0
Recent Progress in Transformer-based Medical Image Analysis—0
Medical Image Denosing via Explainable AI Feature Preserving Loss—0
Adaptive Spatial-Spectral Dictionary Learning for Hyperspectral Image Denoising—0
MedSegDiffNCA: Diffusion Models With Neural Cellular Automata for Skin Lesion Segmentation—0
Adaptive Segmentation-Based Initialization for Steered Mixture of Experts Image Regression—0
Megapixel Photon-Counting Color Imaging using Quanta Image Sensor—0
Mel-FullSubNet: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR—0
Memoized Online Variational Inference for Dirichlet Process Mixture Models—0
Towards Making the Most of Pre-trained Translation Model for Quality Estimation—0
Towards Memorization-Free Diffusion Models—0
Towards More Accurate Diffusion Model Acceleration with A Timestep Aligner—0
Memory in Plain Sight: Surveying the Uncanny Resemblances of Associative Memories and Diffusion Models—0
Show:102550
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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