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 11011110 of 7282 papers

TitleStatusHype
Data-Centric Learning from Unlabeled Graphs with Diffusion ModelCode1
Dynamic Addition of Noise in a Diffusion Model for Anomaly DetectionCode1
D^2-DPM: Dual Denoising for Quantized Diffusion Probabilistic ModelsCode1
D^4-VTON: Dynamic Semantics Disentangling for Differential Diffusion based Virtual Try-OnCode1
G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo LabellingCode1
Guided Diffusion Model for Adversarial PurificationCode1
Aerial Height Prediction and Refinement Neural Networks with Semantic and Geometric GuidanceCode1
HINet: Half Instance Normalization Network for Image RestorationCode1
Image Denoising Using Green Channel PriorCode1
CutDiffusion: A Simple, Fast, Cheap, and Strong Diffusion Extrapolation MethodCode1
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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