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 2921–2930 of 7282 papers

TitleStatusHype
Evolving Deep Convolutional Neural Networks for Hyperspectral Image Denoising—0
Convolution by Evolution: Differentiable Pattern Producing Networks—0
Evolvable Conditional Diffusion—0
Filter Forests for Learning Data-Dependent Convolutional Kernels—0
Evolution Meets Diffusion: Efficient Neural Architecture Generation—0
Financial Market Directional Forecasting With Stacked Denoising Autoencoder—0
ASGDiffusion: Parallel High-Resolution Generation with Asynchronous Structure Guidance—0
A fast patch-dictionary method for whole image recovery—0
Evolutionary Variational Optimization of Generative Models—0
EventZoom: Learning To Denoise and Super Resolve Neuromorphic Events—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