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 4271–4280 of 7282 papers

TitleStatusHype
HiddenSinger: High-Quality Singing Voice Synthesis via Neural Audio Codec and Latent Diffusion Models—0
Generative Plug and Play: Posterior Sampling for Inverse ProblemsCode0
A Deep Unrolling Model with Hybrid Optimization Structure for Hyperspectral Image Deconvolution—0
One-shot Learning for Channel Estimation in Massive MIMO Systems—0
Motion-DVAE: Unsupervised learning for fast human motion denoising—0
Boosting Fast and High-Quality Speech Synthesis with Linear Diffusion—0
Multi-Architecture Multi-Expert Diffusion Models—0
Convolutional Recurrent Neural Network with Attention for 3D Speech Enhancement—0
Complexity-aware Large Scale Origin-Destination Network Generation via Diffusion Model—0
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping—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