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 2776–2800 of 7282 papers

TitleStatusHype
Exploiting Temporal Attention Features for Effective Denoising in Videos—0
Correlation Preserving Sparse Coding Over Multi-level Dictionaries for Image Denoising—0
Extending DNN-based Multiplicative Masking to Deep Subband Filtering for Improved Dereverberation—0
Extending the Use of MDL for High-Dimensional Problems: Variable Selection, Robust Fitting, and Additive Modeling—0
Extensions to the Proximal Distance Method of Constrained Optimization—0
External Knowledge Enhanced 3D Scene Generation from Sketch—0
External Patch Prior Guided Internal Clustering for Image Denoising—0
ActionDiffusion: An Action-aware Diffusion Model for Procedure Planning in Instructional Videos—0
From Noise Modeling to Blind Image Denoising—0
Extracting Information-rich Part of Texts using Text Denoising—0
Exploiting network optimization stability for enhanced PET image denoising using deep image prior—0
Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning—0
Extreme Low-Light Environment-Driven Image Denoising Over Permanently Shadowed Lunar Regions With a Physical Noise Model—0
Cross-boosting of WNNM Image Denoising method by Directional Wavelet Packets—0
Eye-Movement behavior identification for AD diagnosis—0
Correlation Distance Skip Connection Denoising Autoencoder (CDSK-DAE) for Speech Feature Enhancement—0
Cross-conditioned Diffusion Model for Medical Image to Image Translation—0
Exploiting Multilingualism in Low-resource Neural Machine Translation via Adversarial Learning—0
FabricDiffusion: High-Fidelity Texture Transfer for 3D Garments Generation from In-The-Wild Clothing Images—0
Assessing the Impact of Deep Neural Network-based Image Denoising on Binary Signal Detection Tasks—0
A Poisson-Guided Decomposition Network for Extreme Low-Light Image Enhancement—0
Exploiting Model Sparsity in Adaptive MPC: A Compressed Sensing Viewpoint—0
FacEnhance: Facial Expression Enhancing with Recurrent DDPMs—0
FaceShield: Defending Facial Image against Deepfake Threats—0
Correction by Projection: Denoising Images with Generative Adversarial Networks—0
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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