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 5676–5700 of 7282 papers

TitleStatusHype
Improving Speech Enhancement Performance by Leveraging Contextual Broad Phonetic Class Information—0
Channel Estimation for Large Intelligent Surface Aided MISO Communications: From LMMSE to Deep Learning Solutions—0
DANAE: a denoising autoencoder for underwater attitude estimationCode0
Noise2Stack: Improving Image Restoration by Learning from Volumetric Data—0
ESPnet-se: end-to-end speech enhancement and separation toolkit designed for asr integration—0
A Comprehensive Comparison of Multi-Dimensional Image Denoising MethodsCode0
Do Noises Bother Human and Neural Networks In the Same Way? A Medical Image Analysis Perspective—0
Noise Reduction to Compute Tissue Mineral Density and Trabecular Bone Volume Fraction from Low Resolution QCT—0
Generating Synthetic Data for Task-Oriented Semantic Parsing with Hierarchical Representations—0
A Deep Learning based Detection Method for Combined Integrity-Availability Cyber Attacks in Power System—0
Revisiting Adaptive Convolutions for Video Frame Interpolation—0
Deep Pairwise Hashing for Cold-start RecommendationCode0
PALM: Pre-training an Autoencoding\&Autoregressive Language Model for Context-conditioned Generation—0
Maximum a posteriori signal recovery for optical coherence tomography angiography image generation and denoising—0
RH-Net: Improving Neural Relation Extraction via Reinforcement Learning and Hierarchical Relational SearchingCode0
Learning Sparse Graph Laplacian with K Eigenvector Prior via Iterative GLASSO and Projection—0
D-VDAMP: Denoising-based Approximate Message Passing for Compressive MRICode0
Autoregressive Score Matching—0
Electromagnetic Source Imaging via a Data-Synthesis-Based Convolutional Encoder-Decoder Network—0
Representation Learning for High-Dimensional Data Collection under Local Differential Privacy—0
Compressed Sensing with Invertible Generative Models and Dependent Noise—0
Perceptual Loss based Speech Denoising with an ensemble of Audio Pattern Recognition and Self-Supervised ModelsCode0
Denoising Atmospheric Temperature Measurements Taken by the Mars Science Laboratory on the Martian Surface—0
A novel convolutional neural network model to remove muscle artifacts from EEG—0
Unrolling of Deep Graph Total Variation for Image DenoisingCode0
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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