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 3526–3550 of 7282 papers

TitleStatusHype
WaveDM: Wavelet-Based Diffusion Models for Image RestorationCode1
MP-SENet: A Speech Enhancement Model with Parallel Denoising of Magnitude and Phase SpectraCode2
It's Enough: Relaxing Diagonal Constraints in Linear Autoencoders for RecommendationCode1
ViT-TTS: Visual Text-to-Speech with Scalable Diffusion Transformer—0
Extrapolating Multilingual Understanding Models as Multilingual Generators—0
DiffusionNER: Boundary Diffusion for Named Entity RecognitionCode1
Restore Anything Pipeline: Segment Anything Meets Image RestorationCode1
Sparsity and Coefficient Permutation Based Two-Domain AMP for Image Block Compressed Sensing—0
Why current rain denoising models fail on CycleGAN created rain images in autonomous driving—0
Training Diffusion Models with Reinforcement LearningCode2
DCCRN-KWS: an audio bias based model for noise robust small-footprint keyword spotting—0
Guided Motion Diffusion for Controllable Human Motion Synthesis—0
DiffUCD:Unsupervised Hyperspectral Image Change Detection with Semantic Correlation Diffusion Model—0
Dual-Diffusion: Dual Conditional Denoising Diffusion Probabilistic Models for Blind Super-Resolution Reconstruction in RSIsCode1
Moment Matching Denoising Gibbs SamplingCode0
ISP meets Deep Learning: A Survey on Deep Learning Methods for Image Signal Processing—0
SIDAR: Synthetic Image Dataset for Alignment & RestorationCode0
A quality assurance framework for real-time monitoring of deep learning segmentation models in radiotherapy—0
The probability flow ODE is provably fast—0
Information Screening whilst Exploiting! Multimodal Relation Extraction with Feature Denoising and Multimodal Topic ModelingCode1
Reciprocal Attention Mixing Transformer for Lightweight Image RestorationCode1
PTQD: Accurate Post-Training Quantization for Diffusion ModelsCode1
Adaptive Graph Contrastive Learning for RecommendationCode1
NODE-ImgNet: a PDE-informed effective and robust model for image denoisingCode0
GETMusic: Generating Any Music Tracks with a Unified Representation and Diffusion Framework—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