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

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Showing 2701–2750 of 7282 papers

TitleStatusHype
Generalization through variance: how noise shapes inductive biases in diffusion modelsCode0
Generalized Deep Image to Image RegressionCode0
Generalized Octave Convolutions for Learned Multi-Frequency Image CompressionCode0
Generating observation guided ensembles for data assimilation with denoising diffusion probabilistic modelCode0
Annotated Biomedical Video Generation using Denoising Diffusion Probabilistic Models and Flow FieldsCode0
Diffusion Models for Computational Neuroimaging: A SurveyCode0
Class-Aware Fully-Convolutional Gaussian and Poisson DenoisingCode0
GEC-DePenD: Non-Autoregressive Grammatical Error Correction with Decoupled Permutation and DecodingCode0
Diffusion Models as Masked AutoencodersCode0
Gated Texture CNN for Efficient and Configurable Image DenoisingCode0
Gaussian Gated Linear NetworksCode0
A Dictionary Based Approach for Removing Out-of-Focus BlurCode0
Gated Orthogonal Recurrent Units: On Learning to ForgetCode0
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-DecodingCode0
Global Counterfactual DirectionsCode0
Fuse Your Latents: Video Editing with Multi-source Latent Diffusion ModelsCode0
ADFormer: Aggregation Differential Transformer for Passenger Demand ForecastingCode0
Fully Unsupervised Probabilistic Noise2VoidCode0
Fully Convolutional Network with Multi-Step Reinforcement Learning for Image ProcessingCode0
Fully Adaptive Time-Varying Wave-Shape Model: Applications in Biomedical Signal ProcessingCode0
Diffusion Model for Camouflaged Object DetectionCode0
From Shortcuts to Triggers: Backdoor Defense with Denoised PoECode0
From Patches to Images: A Nonparametric Generative ModelCode0
From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion ModelsCode0
From neural PCA to deep unsupervised learningCode0
Game Theory for Adversarial Attacks and DefensesCode0
CharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image DenoisingCode0
FreeDiff: Progressive Frequency Truncation for Image Editing with Diffusion ModelsCode0
FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural NetworksCode0
Focusing on what to decode and what to train: SOV Decoding with Specific Target Guided DeNoising and Vision Language AdvisorCode0
FOCNet: A Fractional Optimal Control Network for Image DenoisingCode0
Foundation Models For Seismic Data Processing: An Extensive ReviewCode0
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading ComprehensionCode0
GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy ImagesCode0
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series ForecastingCode0
Diffusion Denoising Process for Perceptron Bias in Out-of-distribution DetectionCode0
FlexControl: Computation-Aware ControlNet with Differentiable Router for Text-to-Image GenerationCode0
GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPMCode0
Diffusion Counterfactuals for Image RegressorsCode0
A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGACode0
First image then video: A two-stage network for spatiotemporal video denoisingCode0
Noise-aware Physics-informed Machine Learning for Robust PDE DiscoveryCode0
FiRe: Fixed-points of Restoration Priors for Solving Inverse ProblemsCode0
First line of defense: A robust first layer mitigates adversarial attacksCode0
CoStoDet-DDPM: Collaborative Training of Stochastic and Deterministic Models Improves Surgical Workflow Anticipation and RecognitionCode0
Fingerprint Presentation Attack Detection by Channel-wise Feature DenoisingCode0
Flashlight CNN Image DenoisingCode0
Noise Level Adaptive Diffusion Model for Robust Reconstruction of Accelerated MRICode0
Finding Local Diffusion Schrödinger Bridge using Kolmogorov-Arnold NetworkCode0
Finding Local Diffusion Schrodinger Bridge using Kolmogorov-Arnold NetworkCode0
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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