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 3571–3580 of 7282 papers

TitleStatusHype
Denoising bivariate signals via smoothing and polarization priors—0
Adversarial Signal Denoising with Encoder-Decoder Networks—0
Image Restoration with Locally Selected Class-Adapted Models—0
A Coordinate Descent Approach to Atomic Norm Denoising—0
Energy-Based Processes for Exchangeable Data—0
Image Segmentation and Restoration Using Parametric Contours With Free Endpoints—0
Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering—0
Image Segmentation Using Overlapping Group Sparsity—0
Contrastive CFG: Improving CFG in Diffusion Models by Contrasting Positive and Negative Concepts—0
End-to-End Unsupervised Document Image Blind 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