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 1751–1775 of 7282 papers

TitleStatusHype
Diffuman4D: 4D Consistent Human View Synthesis from Sparse-View Videos with Spatio-Temporal Diffusion Models—0
BudgetFusion: Perceptually-Guided Adaptive Diffusion Models—0
BTS: Back TranScription for Speech-to-Text Post-Processor using Text-to-Speech-to-Text—0
An Empirical Study of ADMM for Nonconvex Problems—0
A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction—0
Acceleration of the PDHGM on strongly convex subspaces—0
Diff-TTSG: Denoising probabilistic integrated speech and gesture synthesis—0
3D Dynamic Point Cloud Denoising via Spatial-Temporal Graph Learning—0
An ELU Network with Total Variation for Image Denoising—0
Bring the Power of Diffusion Model to Defect Detection—0
Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition—0
An Efficient Statistical Method for Image Noise Level Estimation—0
Bring Metric Functions into Diffusion Models—0
Bringing together invertible UNets with invertible attention modules for memory-efficient diffusion models—0
A Decoupled Learning Scheme for Real-world Burst Denoising from Raw Images—0
Brightness-Invariant Tracking Estimation in Tagged MRI—0
Bright-NeRF:Brightening Neural Radiance Field with Color Restoration from Low-light Raw Images—0
Predicting the Radiation Field of Molecular Clouds using Denoising Diffusion Probabilistic Models—0
Diff-TTS: A Denoising Diffusion Model for Text-to-Speech—0
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding—0
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models—0
An Efficient and Robust Method for Chest X-Ray Rib Suppression that Improves Pulmonary Abnormality Diagnosis—0
Bridge the Gap between SNN and ANN for Image Restoration—0
BridgeNets: Student-Teacher Transfer Learning Based on Recursive Neural Networks and its Application to Distant Speech Recognition—0
A Novel DDPM-based Ensemble Approach for Energy Theft Detection in Smart Grids—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