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 31213130 of 7282 papers

TitleStatusHype
Efficient Training for Visual Tracking with Deformable Transformer0
Diffusion Model is Secretly a Training-free Open Vocabulary Semantic SegmenterCode1
Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic ManipulationCode1
Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition0
Diffusion Generative Inverse Design0
Robust Online Classification: From Estimation to Denoising0
Blind Biological Sequence Denoising with Self-Supervised Set Learning0
Are We Using Autoencoders in a Wrong Way?Code0
lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systemsCode1
Diffusion Models with Deterministic Normalizing Flow PriorsCode0
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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