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 2101–2150 of 7282 papers

TitleStatusHype
Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift AlgorithmCode0
Learning-Based Reconstruction of FRI SignalsCode0
Automated characterization of noise distributions in diffusion MRI dataCode0
Learning Better Masking for Better Language Model Pre-trainingCode0
Learned D-AMP: Principled Neural Network based Compressive Image RecoveryCode0
Learned Convolutional Sparse CodingCode0
Learning Deep CNN Denoiser Prior for Image RestorationCode0
Lateral Connections in Denoising Autoencoders Support Supervised LearningCode0
AutoJoin: Efficient Adversarial Training against Gradient-Free Perturbations for Robust Maneuvering via Denoising Autoencoder and Joint LearningCode0
Layered Rendering Diffusion Model for Controllable Zero-Shot Image SynthesisCode0
Deep Decoder: Concise Image Representations from Untrained Non-convolutional NetworksCode0
Deep CSI Learning for Gait Biometric Sensing and RecognitionCode0
Unsupervised dynamic modeling of medical image transformationCode0
Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual NetworkCode0
Educating Text Autoencoders: Latent Representation Guidance via DenoisingCode0
Deep Contrastive Patch-Based Subspace Learning for Camera Image Signal ProcessingCode0
Learning Pixel-Distribution Prior with Wider Convolution for Image DenoisingCode0
Autoencoders, Kernels, and Multilayer Perceptrons for Electron Micrograph Restoration and CompressionCode0
Deep Class Aware DenoisingCode0
Massive Styles Transfer with Limited Labeled DataCode0
Large Graph Signal Denoising with Application to Differential PrivacyCode0
Deep Burst DenoisingCode0
Autoencoder-based prediction of ICU clinical codesCode0
Language Model Preference Evaluation with Multiple Weak EvaluatorsCode0
Language-Aware Multilingual Machine Translation with Self-Supervised LearningCode0
Resurrecting Label Propagation for Graphs with Heterophily and Label NoiseCode0
Language Embeddings for Typology and Cross-lingual Transfer LearningCode0
DeepASL: Kinetic Model Incorporated Loss for Denoising Arterial Spin Labeled MRI via Deep Residual LearningCode0
A Unified View on Graph Neural Networks as Graph Signal DenoisingCode0
A Brief Review of Real-World Color Image DenoisingCode0
Labeling, Cutting, Grouping: an Efficient Text Line Segmentation Method for Medieval ManuscriptsCode0
Language-Guided Diffusion Model for Visual GroundingCode0
Decouple Learning for Parameterized Image OperatorsCode0
Kronecker-structured Sparse Vector Recovery with Application to IRS-MIMO Channel EstimationCode0
Airfoil Diffusion: Denoising Diffusion Model For Conditional Airfoil GenerationCode0
Knowledge Enhanced Multi-intent Transformer Network for RecommendationCode0
Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural networkCode0
Adaptive Bayesian Multivariate Spline Knot Inference with Prior Specifications on Model ComplexityCode0
k-Sparse AutoencodersCode0
Aircraft engines Remaining Useful Life prediction with an adaptive denoising online sequential Extreme Learning MachineCode0
Decomposition of Higher-Order Spectra for Blind Multiple-Input Deconvolution, Pattern Identification and SeparationCode0
Joint Visual Denoising and Classification using Deep LearningCode0
KADEL: Knowledge-Aware Denoising Learning for Commit Message GenerationCode0
AIM2PC: Aerial Image to 3D Building Point Cloud ReconstructionCode0
Joint Multi-Scale Tone Mapping and Denoising for HDR Image EnhancementCode0
Decoding the shift-invariant data: applications for band-excitation scanning probe microscopyCode0
Decoding Phone Pairs from MEG Signals Across Speech ModalitiesCode0
Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source SeparationCode0
Learning Priors in High-frequency Domain for Inverse Imaging ReconstructionCode0
Audio Word2Vec: Unsupervised Learning of Audio Segment Representations using Sequence-to-sequence AutoencoderCode0
Show:102550
← PrevPage 43 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