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 2251–2260 of 7282 papers

TitleStatusHype
Bayesian ECG reconstruction using denoising diffusion generative models—0
Adaptive Feature Discrimination and Denoising for Asymmetric Text Matching—0
DeepSpace: Dynamic Spatial and Source Cue Based Source Separation for Dialog Enhancement—0
Bayesian Cramér-Rao Bound Estimation with Score-Based Models—0
Almost Unsupervised Text to Speech and Automatic Speech Recognition—0
Accelerated graph-based spectral polynomial filters—0
Efficient Neural Music Generation—0
Computationally efficient reductions between some statistical models—0
Bayesian Conditional GAN for MRI Brain Image Synthesis—0
Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoising—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