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 776–800 of 7282 papers

TitleStatusHype
DenoMamba: A fused state-space model for low-dose CT denoisingCode1
4DenoiseNet: Adverse Weather Denoising from Adjacent Point CloudsCode1
EdiBERT, a generative model for image editingCode1
AKDT: Adaptive Kernel Dilation Transformer for Effective Image DenoisingCode1
Beyond Image Prior: Embedding Noise Prior into Conditional Denoising TransformerCode1
DenoSent: A Denoising Objective for Self-Supervised Sentence Representation LearningCode1
EEG Synthetic Data Generation Using Probabilistic Diffusion ModelsCode1
Adaptive Consistency Prior Based Deep Network for Image DenoisingCode1
Autoencoders that don't overfit towards the IdentityCode1
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and ComprehensionCode1
Efficient Diffusion Transformer with Step-wise Dynamic Attention MediatorsCode1
A Latent Space of Stochastic Diffusion Models for Zero-Shot Image Editing and GuidanceCode1
Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) and Its Application to Inverse ProblemsCode1
Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data HidingCode1
EGC: Image Generation and Classification via a Diffusion Energy-Based ModelCode1
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion GenerationCode1
E-MLB: Multilevel Benchmark for Event-Based Camera DenoisingCode1
End-to-End Learning for Joint Image Demosaicing, Denoising and Super-ResolutionCode1
AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool UseCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
Adaptive Deep PnP Algorithm for Video Snapshot Compressive ImagingCode1
Denoising Normalizing FlowCode1
EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion ModelsCode1
Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidenceCode1
Denoising MCMC for Accelerating Diffusion-Based Generative ModelsCode1
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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