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 351360 of 7282 papers

TitleStatusHype
CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors0
Fast Autoregressive Models for Continuous Latent Generation0
Self-Supervised Noise Adaptive MRI Denoising via Repetition to Repetition (Rep2Rep) Learning0
A Machine Learning Approach for Denoising and Upsampling HRTFs0
Evolution Meets Diffusion: Efficient Neural Architecture Generation0
ECGDeDRDNet: A deep learning-based method for Electrocardiogram noise removal using a double recurrent dense network0
Diffusion Probabilistic Models for Compressive SAR Imaging0
Physics-guided and fabrication-aware inverse design of photonic devices using diffusion modelsCode1
Survey of Video Diffusion Models: Foundations, Implementations, and ApplicationsCode1
Self-Controlled Diffusion for Denoising in Scientific Imaging0
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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