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 621630 of 7282 papers

TitleStatusHype
Digging into contrastive learning for robust depth estimation with diffusion modelsCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
Adaptive Consistency Prior Based Deep Network for Image DenoisingCode1
Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure TimesCode1
Discrete Contrastive Diffusion for Cross-Modal Music and Image GenerationCode1
Diffusive Gibbs SamplingCode1
AKDT: Adaptive Kernel Dilation Transformer for Effective Image DenoisingCode1
DIFFVSGG: Diffusion-Driven Online Video Scene Graph GenerationCode1
Controlling Latent Diffusion Using Latent CLIPCode1
Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct SupervisionCode1
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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