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 24812490 of 7282 papers

TitleStatusHype
Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth0
Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration0
Context-Aware Automated Passenger Counting Data Denoising0
Denoising Diffusion Probabilistic Models in Six Simple Steps0
Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object DetectionCode2
Unified Discrete Diffusion for Categorical DataCode1
Pard: Permutation-Invariant Autoregressive Diffusion for Graph GenerationCode1
Controllable Diverse Sampling for Diffusion Based Motion Behavior Forecasting0
SDEMG: Score-based Diffusion Model for Surface Electromyographic Signal DenoisingCode1
On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models0
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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