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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 871–880 of 7282 papers

Title	Date	Tasks	Status	Hype
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction	Nov 18, 2022	DenoisingMolecular Property Prediction	CodeCode Available	1
Better Diffusion Models Further Improve Adversarial Training	Feb 9, 2023	Denoising	CodeCode Available	1
Graph Collaborative Signals Denoising and Augmentation for Recommendation	Apr 6, 2023	Collaborative FilteringDenoising	CodeCode Available	1
Graph Denoising Diffusion for Inverse Protein Folding	Jun 29, 2023	DenoisingProtein Folding	CodeCode Available	1
Designing and Training of A Dual CNN for Image Denoising	Jul 8, 2020	DenoisingImage Denoising	CodeCode Available	1
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling	May 27, 2019	DenoisingGenerative Adversarial Network	CodeCode Available	1
G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling	Sep 28, 2020	Contrastive LearningDenoising	CodeCode Available	1
G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling	Sep 25, 2020	Contrastive LearningDenoising	CodeCode Available	1
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs	Dec 7, 2023	AnatomyAnomaly Detection	CodeCode Available	1
DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative Refinement	Sep 10, 2024	Code GenerationDenoising	CodeCode Available	1

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All datasets Darmstadt Noise Dataset DIV2K DND iris

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SINDy	PSNR	81	—	Unverified
2	Pixel-shuffling Downsampling	PSNR	38.4	—	Unverified
3	TWSC	PSNR	37.93	—	Unverified
4	CBDNet(Syn)	PSNR	37.57	—	Unverified
5	MCWNNM	PSNR	37.38	—	Unverified
6	Han et al	PSNR	35.95	—	Unverified
7	FFDNet	PSNR	34.4	—	Unverified
8	TNRD	PSNR	33.65	—	Unverified
9	CDnCNN-B	PSNR	32.43	—	Unverified
10	NLRN	PSNR	30.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DRUnet_Poisson_0.01	Average PSNR (dB)	33.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DRANet	Average PSNR	39.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PCNN+RL+HME	Average	84.61	—	Unverified