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 2781–2790 of 7282 papers

Title	Date	Tasks	Status	Score
Few-shot point cloud reconstruction and denoising via learned Guassian splats renderings and fine-tuned diffusion features	Apr 1, 2024	3D ReconstructionDeep Learning	CodeCode Available	5
Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure Prediction	Aug 20, 2022	DenoisingFew-Shot Learning	CodeCode Available	5
FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising	Oct 11, 2017	Color Image DenoisingCPU	CodeCode Available	5
DiffuseDef: Improved Robustness to Adversarial Attacks via Iterative Denoising	Jun 28, 2024	Adversarial DefenseDenoising	CodeCode Available	5
DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesis	Mar 24, 2023	DenoisingIndoor Scene Synthesis	CodeCode Available	5
DiffuPose: Monocular 3D Human Pose Estimation via Denoising Diffusion Probabilistic Model	Dec 6, 2022	3D Human Pose EstimationDenoising	CodeCode Available	5
CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion Models	Feb 1, 2025	DenoisingImage Generation	CodeCode Available	5
Few-shot Image Generation with Diffusion Models	Nov 7, 2022	DenoisingDiversity	CodeCode Available	5
Accurate Segmentation of Optic Disc And Cup from Multiple Pseudo-labels by Noise-aware Learning	Nov 30, 2023	DenoisingSegmentation	CodeCode Available	5
FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising	Apr 2, 2023	DenoisingFederated Learning	CodeCode Available	5

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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