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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 6901–6925 of 7282 papers

TitleStatusHype
Enhancing Diffusion Models for Inverse Problems with Covariance-Aware Posterior Sampling—0
Enhancing Diffusion Posterior Sampling for Inverse Problems by Integrating Crafted Measurements—0
SurGrID: Controllable Surgical Simulation via Scene Graph to Image Diffusion—0
Enhancing Few-Shot Stock Trend Prediction with Large Language Models—0
Enhancing GANs with Contrastive Learning-Based Multistage Progressive Finetuning SNN and RL-Based External Optimization—0
Enhancing Glass Defect Detection with Diffusion Models: Addressing Imbalanced Datasets in Manufacturing Quality Control—0
Survey: Machine Learning in Production Rendering—0
Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models—0
Enhancing Low Light Videos by Exploring High Sensitivity Camera Noise—0
Enhancing Medical Image Segmentation with Deep Learning and Diffusion Models—0
Survey of Deep Learning Methods for Inverse Problems—0
Enhancing Motion Dynamics of Image-to-Video Models via Adaptive Low-Pass Guidance—0
Enhancing Real-World Active Speaker Detection with Multi-Modal Extraction Pre-Training—0
Enhancing Recommendation with Denoising Auxiliary Task—0
VIPaint: Image Inpainting with Pre-Trained Diffusion Models via Variational Inference—0
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
Enhancing super-resolution ultrasound localisation through multi-frame deconvolution exploiting spatiotemporal coherence—0
Enhancing Text-to-Image Diffusion Transformer via Split-Text Conditioning—0
Enhancing the prediction of disease outcomes using electronic health records and pretrained deep learning models—0
Enhancing Underwater Image via Adaptive Color and Contrast Enhancement, and Denoising—0
Ensemble Noise Simulation to Handle Uncertainty about Gradient-based Adversarial Attacks—0
Survey on LiDAR Perception in Adverse Weather Conditions—0
ENSURE: A General Approach for Unsupervised Training of Deep Image Reconstruction Algorithms—0
ISP meets Deep Learning: A Survey on Deep Learning Methods for Image Signal Processing—0
Entropy stable conservative flux form neural 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