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 2371–2380 of 7282 papers

TitleStatusHype
Ambient Denoising Diffusion Generative Adversarial Networks for Establishing Stochastic Object Models from Noisy Image Data—0
Principal Components for Neural Network InitializationCode0
CoSTI: Consistency Models for (a faster) Spatio-Temporal ImputationCode0
Collaborative Diffusion Model for Recommender System—0
PSyDUCK: Training-Free Steganography for Latent Diffusion—0
Task-based Regularization in Penalized Least-Squares for Binary Signal Detection Tasks in Medical Image Denoising—0
From Data to Action: Charting A Data-Driven Path to Combat Antimicrobial Resistance—0
Music2Latent2: Audio Compression with Summary Embeddings and Autoregressive Decoding—0
Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation—0
Variational Schrödinger Momentum Diffusion—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