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
Missing Data Imputation with Adversarially-trained Graph Convolutional NetworksCode0
A deep convolutional neural network for salt-and-pepper noise removal using selective convolutional blocksCode0
Misaligned Over-The-Air Computation of Multi-Sensor Data with Wiener-Denoiser NetworkCode0
Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain GeneralizationCode0
An Efficient End-to-End Approach to Noise Invariant Speech Features via Multi-Task LearningCode0
Acceleration of RED via Vector ExtrapolationCode0
MFTF: Mask-free Training-free Object Level Layout Control Diffusion ModelCode0
Lightweight network towards real-time image denoising on mobile devicesCode0
Addressing Small and Imbalanced Medical Image Datasets Using Generative Models: A Comparative Study of DDPM and PGGANs with Random and Greedy K SamplingCode0
MFM-DA: Instance-Aware Adaptor and Hierarchical Alignment for Efficient Domain Adaptation in Medical Foundation ModelsCode0
Mesh Denoising with Facet Graph ConvolutionsCode0
Meta-DiffuB: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-ExplorationCode0
Metaphor Detection with Effective Context DenoisingCode0
Microscopy Image Restoration with Deep Wiener-Kolmogorov filtersCode0
Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision TransformersCode0
Brain-like Flexible Visual Inference by Harnessing Feedback-Feedforward AlignmentCode0
Megapixel Image Generation with Step-Unrolled Denoising AutoencodersCode0
A Semi-Supervised Approach for Low-Resourced Text GenerationCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and EnhancementCode0
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Frame Interpolation and EnhancementCode0
BrainCodec: Neural fMRI codec for the decoding of cognitive brain statesCode0
An Automated Pipeline for Few-Shot Bird Call Classification: A Case Study with the Tooth-Billed PigeonCode0
Addressing Missing Data Issue for Diffusion-based RecommendationCode0
MicroSSIM: Improved Structural Similarity for Comparing Microscopy DataCode0
An Attention-Based Denoising Framework for Personality Detection in Social Media TextsCode0
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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