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 161–170 of 7282 papers

TitleStatusHype
Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models—0
Rhetorical Text-to-Image Generation via Two-layer Diffusion Policy Optimization—0
Leveraging Diffusion Models for Synthetic Data Augmentation in Protein Subcellular Localization Classification—0
Shapley Value-driven Data Pruning for Recommender SystemsCode0
Kernel-Smoothed Scores for Denoising Diffusion: A Bias-Variance Study—0
GLAMP: An Approximate Message Passing Framework for Transfer Learning with Applications to Lasso-based Estimators—0
Plug-and-Play Posterior Sampling for Blind Inverse Problems—0
ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning—0
Algorithm Unrolling-based Denoising of Multimodal Graph Signals—0
Autoencoding Random Forests—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