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 3621–3630 of 7282 papers

TitleStatusHype
Iso-Diffusion: Improving Diffusion Probabilistic Models Using the Isotropy of the Additive Gaussian Noise—0
Improved Sparse Low-Rank Matrix Estimation—0
Continuous Optimization for Fields of Experts Denoising Works—0
End-to-End Adaptive Monte Carlo Denoising and Super-Resolution—0
InSAR Phase Denoising: A Review of Current Technologies and Future Directions—0
Improving Adversarial Energy-Based Model via Diffusion Process—0
END: Early Noise Dropping for Efficient and Effective Context Denoising—0
END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation—0
Improving Audio-Visual Video Parsing with Pseudo Visual Labels—0
Continuous Modeling of the Denoising Process for Speech Enhancement Based on Deep Learning—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