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 5401–5450 of 7282 papers

TitleStatusHype
Sparta: Spatially Attentive and Adversarially Robust Activations—0
Three-quarter Sibling Regression for Denoising Observational Data—0
Conditional Generation of Temporally-ordered Event Sequences—0
Revisiting Robust Neural Machine Translation: A Transformer Case Study—0
Promoting Graph Awareness in Linearized Graph-to-Text Generation—0
NBNet: Noise Basis Learning for Image Denoising with Subspace ProjectionCode1
Denoising quantum states with Quantum Autoencoders -- Theory and ApplicationsCode0
A Plug-and-Play Priors Framework for Hyperspectral UnmixingCode0
Memory-Efficient Hierarchical Neural Architecture Search for Image RestorationCode1
Towards Boosting the Channel Attention in Real Image Denoising : Sub-band Pyramid Attention—0
HDR Denoising and Deblurring by Learning Spatio-temporal Distortion Models—0
Modeling Deep Learning Based Privacy Attacks on Physical MailCode1
Evolutionary Variational Optimization of Generative Models—0
Time-Travel RephotographyCode1
Improving J-divergence of brain connectivity states by graph Laplacian denoising—0
Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift AlgorithmCode0
Memory AMPCode1
Visual Speech Enhancement Without A Real Visual StreamCode1
Object Detection based on OcSaFPN in Aerial Images with Noise—0
A Survey on the Visual Perceptions of Gaussian Noise Filtering on Photography—0
Revisit 1D Total Variation restoration problem with new real-time algorithms for signal and hyper-parameter estimationsCode0
Denoising Text to Speech with Frame-Level Noise Modeling—0
Relightable 3D Head Portraits from a Smartphone Video—0
On the Limitations of Denoising Strategies as Adversarial Defenses—0
Projected Distribution Loss for Image EnhancementCode0
TEMImageNet Training Library and AtomSegNet Deep-Learning Models for High-Precision Atom Segmentation, Localization, Denoising, and Super-Resolution Processing of Atomic-Resolution Images—0
Mesh Denoising with Facet Graph ConvolutionsCode0
On Low-Rank Hankel Matrix Denoising—0
Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-EncodersCode1
Knowledge Capture and Replay for Continual Learning—0
D2-Net: Weakly-Supervised Action Localization via Discriminative Embeddings and Denoised ActivationsCode0
Online Joint Topology Identification and Signal Estimation from Streams with Missing Data—0
Denoising-based Turbo Message Passing for Compressed Video Background Subtraction—0
An Empirical Review of Adversarial DefensesCode0
Deep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments—0
Convex Regularization Behind Neural Reconstruction—0
Learning Medical Image Denoising with Deep Dynamic Residual Attention NetworkCode1
Color Image Restoration Exploiting Inter-channel Correlation with a 3-stage CNNCode0
Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning—0
Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering—0
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading ComprehensionCode0
Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure TimesCode1
Towards speech enhancement using a variational U-Net architecture—0
H-FND: Hierarchical False-Negative Denoising for Distant Supervision Relation ExtractionCode0
Noise2Kernel: Adaptive Self-Supervised Blind Denoising using a Dilated Convolutional Kernel Architecture—0
A Pseudo-labelling Auto-Encoder for unsupervised image classification—0
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation—0
Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals—0
Event Guided Denoising for Multilingual Relation Learning—0
Lookahead optimizer improves the performance of Convolutional Autoencoders for reconstruction of natural images—0
Show:102550
← PrevPage 109 of 146Next →
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