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 2051–2060 of 7282 papers

TitleStatusHype
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods—0
Directly Denoising Diffusion Models—0
Adaptive Bayesian Multivariate Spline Knot Inference with Prior Specifications on Model ComplexityCode0
MetaEarth: A Generative Foundation Model for Global-Scale Remote Sensing Image Generation—0
Prompt Mixing in Diffusion Models using the Black Scholes AlgorithmCode0
Conditioning diffusion models by explicit forward-backward bridgingCode0
DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech TranslationCode0
Hybrid Digital-Analog Semantic Communications—0
DARK: Denoising, Amplification, Restoration KitCode0
Kernel spectral joint embeddings for high-dimensional noisy datasets using duo-landmark integral operators—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