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 811820 of 7282 papers

TitleStatusHype
3D^2-Actor: Learning Pose-Conditioned 3D-Aware Denoiser for Realistic Gaussian Avatar ModelingCode1
Autoregressive Diffusion Model for Graph GenerationCode1
4D Facial Expression Diffusion ModelCode1
Denoising Diffusion Recommender ModelCode1
ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT DenoisingCode1
Efficient Diffusion Transformer with Step-wise Dynamic Attention MediatorsCode1
Aligning Few-Step Diffusion Models with Dense Reward Difference LearningCode1
A Variational Perspective on Solving Inverse Problems with Diffusion ModelsCode1
Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) and Its Application to Inverse ProblemsCode1
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion GenerationCode1
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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