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 601–625 of 7282 papers

TitleStatusHype
Adaptive Differential Denoising for Respiratory Sounds ClassificationCode1
CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-ThoughtCode1
Discrete Diffusion Probabilistic Models for Symbolic Music GenerationCode1
Convolutional Proximal Neural Networks and Plug-and-Play AlgorithmsCode1
Discovering Interpretable Directions in the Semantic Latent Space of Diffusion ModelsCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding OptimizationCode1
Discrete Contrastive Diffusion for Cross-Modal Music and Image GenerationCode1
DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image GenerationCode1
Divide-and-Conquer Posterior Sampling for Denoising Diffusion PriorsCode1
Adaptive Deep PnP Algorithm for Video Snapshot Compressive ImagingCode1
DiffX: Guide Your Layout to Cross-Modal Generative ModelingCode1
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based PenaltiesCode1
DiFSD: Ego-Centric Fully Sparse Paradigm with Uncertainty Denoising and Iterative Refinement for Efficient End-to-End Self-DrivingCode1
Digging into contrastive learning for robust depth estimation with diffusion modelsCode1
Adaptive Cross-Layer Attention for Image RestorationCode1
A Latent Space of Stochastic Diffusion Models for Zero-Shot Image Editing and GuidanceCode1
Diffusive Gibbs SamplingCode1
Adaptive Consistency Prior Based Deep Network for Image DenoisingCode1
Controlling Latent Diffusion Using Latent CLIPCode1
DIFFVSGG: Diffusion-Driven Online Video Scene Graph GenerationCode1
Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure TimesCode1
AKDT: Adaptive Kernel Dilation Transformer for Effective Image DenoisingCode1
Diffusion Suction Grasping with Large-Scale Parcel DatasetCode1
Contrastive Denoising Score for Text-guided Latent Diffusion Image EditingCode1
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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