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 2101–2110 of 7282 papers

TitleStatusHype
Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering—0
Denoising Click-evoked Otoacoustic Emission Signals by Optimal Shrinkage—0
The Missing U for Efficient Diffusion Models—0
Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling—0
A multi-artifact EEG denoising by frequency-based deep learning—0
Denoising bivariate signals via smoothing and polarization priors—0
3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network—0
Denoising-based UNMT is more robust to word-order divergence than MASS-based UNMT—0
Denoising-based Turbo Message Passing for Compressed Video Background Subtraction—0
DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM—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