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 4031–4040 of 7282 papers

TitleStatusHype
GeoDirDock: Guiding Docking Along Geodesic Paths—0
GeoGCN: Geometric Dual-domain Graph Convolution Network for Point Cloud Denoising—0
Geometric and Learning-based Mesh Denoising: A Comprehensive Survey—0
Geometric Constraints in Probabilistic Manifolds: A Bridge from Molecular Dynamics to Structured Diffusion Processes—0
Geometric Machine Learning on EEG Signals—0
Geometry-Aware Neighborhood Search for Learning Local Models for Image Reconstruction—0
Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection—0
Geophysical inverse problems with measurement-guided diffusion models—0
GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining—0
Adversarial Defense via Image Denoising with Chaotic Encryption—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