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 2026–2050 of 7282 papers

TitleStatusHype
CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors—0
Fast Autoregressive Models for Continuous Latent Generation—0
Diffusion Probabilistic Models for Compressive SAR Imaging—0
ECGDeDRDNet: A deep learning-based method for Electrocardiogram noise removal using a double recurrent dense network—0
An Automated Pipeline for Few-Shot Bird Call Classification: A Case Study with the Tooth-Billed PigeonCode0
Self-Controlled Diffusion for Denoising in Scientific Imaging—0
Aerial Active STAR-RIS-assisted Satellite-Terrestrial Covert Communications—0
PIV-FlowDiffuser:Transfer-learning-based denoising diffusion models for PIVCode0
Learned Primal Dual Splitting for Self-Supervised Noise-Adaptive MRI Reconstruction—0
DyST-XL: Dynamic Layout Planning and Content Control for Compositional Text-to-Video Generation—0
A Self-supervised Learning Method for Raman Spectroscopy based on Masked Autoencoders—0
FlowLoss: Dynamic Flow-Conditioned Loss Strategy for Video Diffusion Models—0
An Artificial Intelligence Enabled Signature Estimation of Dual Wideband Systems in Ultra-Low Signal-to-Noise Ratio—0
Text-Audio-Visual-conditioned Diffusion Model for Video Saliency Prediction—0
Generative emulation of chaotic dynamics with coherent prior—0
Adaptive Long-term Embedding with Denoising and Augmentation for RecommendationCode0
Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving SafetyCode0
OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone InscriptionsCode0
Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir Computing—0
Generalization through variance: how noise shapes inductive biases in diffusion modelsCode0
Modality-Independent Explainable Detection of Inaccurate Organ Segmentations Using Denoising Autoencoders—0
Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis—0
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging—0
Generative Recommendation with Continuous-Token Diffusion—0
Exploring Video-Based Driver Activity Recognition under Noisy LabelsCode0
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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