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 2621–2630 of 7282 papers

TitleStatusHype
A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond—0
A Survey on Hyperspectral Image Restoration: From the View of Low-Rank Tensor Approximation—0
A Generative Adversarial Approach with Residual Learning for Dust and Scratches Artifacts Removal—0
ACT-Net: Anchor-context Action Detection in Surgery Videos—0
A Survey on Deep Tabular Learning—0
A Bayesian Hyperprior Approach for Joint Image Denoising and Interpolation, with an Application to HDR Imaging—0
CUNI Submission to MT4All Shared Task—0
A Survey on Deep learning based Document Image Enhancement—0
Fast, Trainable, Multiscale Denoising—0
Parallel Diffusion Model-based Sparse-view Cone-beam Breast CT—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