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 20212030 of 7282 papers

TitleStatusHype
Deep Pairwise Hashing for Cold-start RecommendationCode0
Differentiable Surface Splatting for Point-based Geometry ProcessingCode0
DeepOrientation: convolutional neural network for fringe pattern orientation map estimationCode0
Noisy Batch Active Learning with Deterministic AnnealingCode0
Learning Joint Denoising, Demosaicing, and Compression from the Raw Natural Image Noise DatasetCode0
Path-Restore: Learning Network Path Selection for Image RestorationCode0
Learning Equations from Biological Data with Limited Time SamplesCode0
Learning Dynamics of Linear Denoising AutoencodersCode0
Learning Generalizable 3D Manipulation With 10 DemonstrationsCode0
Deep Contrastive Patch-Based Subspace Learning for Camera Image Signal ProcessingCode0
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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