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

Showing 45614570 of 7282 papers

TitleStatusHype
The Wasserstein transform0
Diffusion Models for Safety Validation of Autonomous Driving Systems0
Joint Image Compression and Denoising via Latent-Space Scalability0
Joint Localization and Planning using Diffusion0
Thompson Sampling with Diffusion Generative Prior0
Jointly optimal dereverberation and beamforming0
Watch and Learn: Leveraging Expert Knowledge and Language for Surgical Video Understanding0
Joint multiband deconvolution for Euclid and Vera C. Rubin images0
Three dimensional blind image deconvolution for fluorescence microscopy using generative adversarial networks0
An Interpretable Joint Nonnegative Matrix Factorization-Based Point Cloud Distance Measure0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified