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 2601–2625 of 7282 papers

TitleStatusHype
Efficiency Meets Fidelity: A Novel Quantization Framework for Stable Diffusion—0
Echocardiography to Cardiac MRI View Transformation for Real-Time Blind Restoration—0
Diverse Score Distillation—0
Generative Lines Matching Models—0
CARP: Visuomotor Policy Learning via Coarse-to-Fine Autoregressive Prediction—0
BudgetFusion: Perceptually-Guided Adaptive Diffusion Models—0
Accelerating Video Diffusion Models via Distribution Matching—0
3D-Consistent Image Inpainting with Diffusion Models—0
Tiny Object Detection with Single Point Supervision—0
Adversarial Transferability in Deep Denoising Models: Theoretical Insights and Robustness Enhancement via Out-of-Distribution Typical Set Sampling—0
Enhanced 3D Generation by 2D Editing—0
Graph with Sequence: Broad-Range Semantic Modeling for Fake News Detection—0
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
A Comparative Study of Image Denoising Algorithms—0
The Silent Prompt: Initial Noise as Implicit Guidance for Goal-Driven Image Generation—0
Latent Space Characterization of Autoencoder Variants—0
Equivariant Denoisers for Image Restoration—0
A Data-Driven Framework for Discovering Fractional Differential Equations in Complex Systems—0
Deep priors for satellite image restoration with accurate uncertainties—0
INFP: Audio-Driven Interactive Head Generation in Dyadic Conversations—0
Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image—0
Local Curvature Smoothing with Stein's Identity for Efficient Score Matching—0
SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout—0
A Noise is Worth Diffusion Guidance—0
UTSD: Unified Time Series Diffusion Model—0
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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