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 40714080 of 7282 papers

TitleStatusHype
DeNoising-MOT: Towards Multiple Object Tracking with Severe Occlusions0
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation0
From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion ModelsCode0
MS-UNet-v2: Adaptive Denoising Method and Training Strategy for Medical Image Segmentation with Small Training Data0
Data-Adaptive Graph Framelets with Generalized Vanishing Moments for Graph Signal ProcessingCode0
Efficient Training for Visual Tracking with Deformable Transformer0
Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition0
Diffusion Generative Inverse Design0
Robust Online Classification: From Estimation to Denoising0
Are We Using Autoencoders in a Wrong Way?Code0
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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