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

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Showing 3171–3180 of 7282 papers

TitleStatusHype
Temporal Residual Guided Diffusion Framework for Event-Driven Video Reconstruction—0
2D Neural Fields with Learned Discontinuities—0
Pre-training with Fractional Denoising to Enhance Molecular Property Prediction—0
Unsupervised Anomaly Detection Using Diffusion Trend Analysis—0
Fast and Robust Phase Retrieval via Deep Expectation-Consistent ApproximationCode0
Enhancing Few-Shot Stock Trend Prediction with Large Language Models—0
ECG Signal Denoising Using Multi-scale Patch Embedding and Transformers—0
DG-PIC: Domain Generalized Point-In-Context Learning for Point Cloud Understanding—0
Haar Nuclear Norms with Applications to Remote Sensing Imagery Restoration—0
Live2Diff: Live Stream Translation via Uni-directional Attention in Video Diffusion Models—0
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified