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 726–750 of 7282 papers

TitleStatusHype
DAS-N2N: Machine learning Distributed Acoustic Sensing (DAS) signal denoising without clean dataCode1
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based PenaltiesCode1
ECG-Image-Kit: A Synthetic Image Generation Toolbox to Facilitate Deep Learning-Based Electrocardiogram DigitizationCode1
A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal RecommendationCode1
Dual-Domain Coarse-to-Fine Progressive Estimation Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECTCode1
A text-based, generative deep learning model for soil reflectance spectrum simulation in the VIS-NIR (400-2499 nm) bandsCode1
DCT2net: an interpretable shallow CNN for image denoisingCode1
A Simple and Robust Correlation Filtering Method for Text-based Person SearchCode1
Controlling Latent Diffusion Using Latent CLIPCode1
Dual convolutional neural network with attention for image blind denoisingCode1
DualDiff+: Dual-Branch Diffusion for High-Fidelity Video Generation with Reward GuidanceCode1
DTP-Net: Learning to Reconstruct EEG signals in Time-Frequency Domain by Multi-scale Feature ReuseCode1
Action-Conditioned 3D Human Motion Synthesis with Transformer VAECode1
Dual Adversarial Network: Toward Real-world Noise Removal and Noise GenerationCode1
Dual-Diffusion: Dual Conditional Denoising Diffusion Probabilistic Models for Blind Super-Resolution Reconstruction in RSIsCode1
Decoder Denoising Pretraining for Semantic SegmentationCode1
TTS-Portuguese Corpus: a corpus for speech synthesis in Brazilian PortugueseCode1
Dual Prior Unfolding for Snapshot Compressive ImagingCode1
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Contrastive Denoising Score for Text-guided Latent Diffusion Image EditingCode1
Enhancing Creative Generation on Stable Diffusion-based ModelsCode1
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
DriveGEN: Generalized and Robust 3D Detection in Driving via Controllable Text-to-Image Diffusion GenerationCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
Continual Learning of Diffusion Models with Generative DistillationCode1
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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