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 42214230 of 7282 papers

TitleStatusHype
Evaluating Unsupervised Denoising Requires Unsupervised MetricsCode0
GENIE: Higher-Order Denoising Diffusion SolversCode1
Instance Regularization for Discriminative Language Model Pre-trainingCode0
Markup-to-Image Diffusion Models with Scheduled SamplingCode1
A generic diffusion-based approach for 3D human pose prediction in the wildCode1
Retinex Image Enhancement Based on Sequential Decomposition With a Plug-and-Play Framework0
Denoising Masked AutoEncoders Help Robust ClassificationCode1
Masked Autoencoders for Low dose CT denoising0
CLIP-Diffusion-LM: Apply Diffusion Model on Image CaptioningCode1
What the DAAM: Interpreting Stable Diffusion Using Cross AttentionCode2
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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