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 14311440 of 7282 papers

TitleStatusHype
Estimating Atmospheric Variables from Digital Typhoon Satellite Images via Conditional Denoising Diffusion ModelsCode1
Curriculum Disentangled Recommendation with Noisy Multi-feedbackCode1
On Memorization in Diffusion ModelsCode1
On the Asymptotic Mean Square Error Optimality of Diffusion ModelsCode1
IterativePFN: True Iterative Point Cloud FilteringCode1
Decoder Denoising Pretraining for Semantic SegmentationCode1
Customizing 360-Degree Panoramas through Text-to-Image Diffusion ModelsCode1
CutDiffusion: A Simple, Fast, Cheap, and Strong Diffusion Extrapolation MethodCode1
ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image PriorCode1
It's Enough: Relaxing Diagonal Constraints in Linear Autoencoders for RecommendationCode1
Show:102550
← PrevPage 144 of 729Next →

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