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 976–1000 of 7282 papers

TitleStatusHype
LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse DiffusionCode1
Deep Speech Synthesis from MRI-Based Articulatory RepresentationsCode1
ECG-Image-Kit: A Synthetic Image Generation Toolbox to Facilitate Deep Learning-Based Electrocardiogram DigitizationCode1
SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph GenerationCode1
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion ModelsCode1
Spiking Denoising Diffusion Probabilistic ModelsCode1
Graph Denoising Diffusion for Inverse Protein FoldingCode1
DoseDiff: Distance-aware Diffusion Model for Dose Prediction in RadiotherapyCode1
ProRes: Exploring Degradation-aware Visual Prompt for Universal Image RestorationCode1
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
Semi-Implicit Denoising Diffusion Models (SIDDMs)Code1
Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct SupervisionCode1
Masked Diffusion Models Are Fast Distribution LearnersCode1
Multi-Granularity Hand Action DetectionCode1
Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion ModelsCode1
Generative Proxemics: A Prior for 3D Social Interaction from ImagesCode1
Probabilistic-based Feature Embedding of 4-D Light Fields for Compressive Imaging and DenoisingCode1
On the Robustness of Latent Diffusion ModelsCode1
Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned GenerationCode1
3D molecule generation by denoising voxel gridsCode1
Diffusion Models for Black-Box OptimizationCode1
VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion ModelsCode1
Beyond Surface Statistics: Scene Representations in a Latent Diffusion ModelCode1
ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion ProcessCode1
Protein Discovery with Discrete Walk-Jump SamplingCode1
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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