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

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Showing 4601–4650 of 7282 papers

TitleStatusHype
The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models—0
Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial TrainingCode1
Zero-shot Blind Image Denoising via Implicit Neural Representations—0
iSDF: Real-Time Neural Signed Distance Fields for Robot PerceptionCode2
RestoreX-AI: A Contrastive Approach towards Guiding Image Restoration via Explainable AI Systems—0
Estimating Fine-Grained Noise Model via Contrastive Learning—0
Perception Prioritized Training of Diffusion ModelsCode1
SpecGrad: Diffusion Probabilistic Model based Neural Vocoder with Adaptive Noise Spectral Shaping—0
StyleFool: Fooling Video Classification Systems via Style TransferCode1
Modeling Users' Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce SearchCode1
Connections between Deep Equilibrium and Sparse Representation Models with Application to Hyperspectral Image Denoising—0
Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A survey—0
Target and Task specific Source-Free Domain Adaptive Image SegmentationCode1
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentationCode0
Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations—0
Limited Parameter Denoising for Low-dose X-ray Computed Tomography Using Deep Reinforcement Learning—0
Time-inhomogeneous diffusion geometry and topology—0
Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages—0
Reverse Engineering of Imperceptible Adversarial Image PerturbationsCode1
ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 Segmentation—0
Practical Blind Image Denoising via Swin-Conv-UNet and Data SynthesisCode2
On the Kullback-Leibler divergence between pairwise isotropic Gaussian-Markov random fields—0
CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from ImageCode1
MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion—0
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising AutoencodersCode1
ProgressiveMotionSeg: Mutually Reinforced Framework for Event-Based Motion Segmentation—0
AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot NetworkCode1
CRISPnet: Color Rendition ISP Net—0
Optical Fiber Fault Detection and Localization in a Noisy OTDR Trace Based on Denoising Convolutional Autoencoder and Bidirectional Long Short-Term Memory—0
Adversarial Defense via Image Denoising with Chaotic Encryption—0
RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression—0
A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large ShiftCode1
Neural Compression-Based Feature Learning for Video Restoration—0
DU-VLG: Unifying Vision-and-Language Generation via Dual Sequence-to-Sequence Pre-training—0
Diffusion Probabilistic Modeling for Video GenerationCode1
FB-MSTCN: A Full-Band Single-Channel Speech Enhancement Method Based on Multi-Scale Temporal Convolutional Network—0
A Noise-level-aware Framework for PET Image Denoising—0
Representation Learning for Resource-Constrained Keyphrase GenerationCode1
Image Quality Assessment for Magnetic Resonance ImagingCode3
Joint Time-Vertex Fractional Fourier Transform—0
P-STMO: Pre-Trained Spatial Temporal Many-to-One Model for 3D Human Pose EstimationCode1
Graph filtering over expanding graphs—0
Time-series image denoising of pressure-sensitive paint data by projected multivariate singular spectrum analysis—0
Denoising and feature extraction in photoemission spectra with variational auto-encoder neural networks—0
Blind2Unblind: Self-Supervised Image Denoising with Visible Blind SpotsCode1
Change Detection from Synthetic Aperture Radar Images via Dual Path Denoising Network—0
PD-Flow: A Point Cloud Denoising Framework with Normalizing FlowsCode1
Dual reparametrized Variational Generative Model for Time-Series Forecasting—0
Manifold Modeling in Quotient Space: Learning An Invariant Mapping with Decodability of Image Patches—0
Dynamic Dual-Output Diffusion Models—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