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 661670 of 7282 papers

TitleStatusHype
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute0
Finding Local Diffusion Schrödinger Bridge using Kolmogorov-Arnold NetworkCode0
MFSR: Multi-fractal Feature for Super-resolution Reconstruction with Fine Details Recovery0
CleanMel: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASRCode2
cMIM: A Contrastive Mutual Information Framework for Unified Generative and Discriminative Representation Learning0
Noise-Injected Spiking Graph Convolution for Energy-Efficient 3D Point Cloud DenoisingCode1
Attention Distillation: A Unified Approach to Visual Characteristics TransferCode3
END: Early Noise Dropping for Efficient and Effective Context Denoising0
A Dual-Purpose Framework for Backdoor Defense and Backdoor Amplification in Diffusion Models0
Self-supervised conformal prediction for uncertainty quantification in Poisson imaging problems0
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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