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 3341–3350 of 7282 papers

TitleStatusHype
Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models—0
Nuclear Norm Regularization for Deep Learning—0
Visual Echoes: A Simple Unified Transformer for Audio-Visual Generation—0
Bracket Diffusion: HDR Image Generation by Consistent LDR Denoising—0
Combining Denoising Autoencoders with Contrastive Learning to fine-tune Transformer ModelsCode0
Design Editing for Offline Model-based Optimization—0
MetaEarth: A Generative Foundation Model for Global-Scale Remote Sensing Image Generation—0
Adaptive Bayesian Multivariate Spline Knot Inference with Prior Specifications on Model ComplexityCode0
Score-based Generative Models with Adaptive Momentum—0
Conditioning diffusion models by explicit forward-backward bridgingCode0
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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