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 3676–3700 of 7282 papers

TitleStatusHype
Pixel-wise Guidance for Utilizing Auxiliary Features in Monte Carlo DenoisingCode1
DDRF: Denoising Diffusion Model for Remote Sensing Image Fusion—0
A Cheaper and Better Diffusion Language Model with Soft-Masked NoiseCode1
HumanSD: A Native Skeleton-Guided Diffusion Model for Human Image GenerationCode2
Unsupervised Multi-Criteria Adversarial Detection in Deep Image Retrieval—0
SAR2EO: A High-resolution Image Translation Framework with Denoising Enhancement—0
On The Application Of Log Compression and Enhanced Denoising In Contrast Enhancement Of Digital Radiography Images—0
MCDIP-ADMM: Overcoming Overfitting in DIP-based CT reconstruction—0
Harnessing the Spatial-Temporal Attention of Diffusion Models for High-Fidelity Text-to-Image SynthesisCode1
ChiroDiff: Modelling chirographic data with Diffusion Models—0
RED-PSM: Regularization by Denoising of Factorized Low Rank Models for Dynamic ImagingCode0
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit ModelsCode1
Graph Collaborative Signals Denoising and Augmentation for RecommendationCode1
RoSteALS: Robust Steganography using Autoencoder Latent SpaceCode1
Diffusion Models as Masked AutoencodersCode0
Spike Stream Denoising via Spike Camera Simulation—0
Boundary-Denoising for Video Activity LocalizationCode0
Mixed Regression via Approximate Message Passing—0
Self-Supervised Siamese Autoencoders—0
HNeRV: A Hybrid Neural Representation for VideosCode1
A Diffusion-based Method for Multi-turn Compositional Image Generation—0
Goal-Conditioned Imitation Learning using Score-based Diffusion PoliciesCode1
Image Blind Denoising Using Dual Convolutional Neural Network with Skip ConnectionCode0
Denoising Diffusion Probabilistic Models to Predict the Density of Molecular CloudsCode1
EGC: Image Generation and Classification via a Diffusion Energy-Based ModelCode1
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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