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

Showing 751775 of 7282 papers

TitleStatusHype
Ab-initio Contrast Estimation and Denoising of Cryo-EM ImagesCode1
DogLayout: Denoising Diffusion GAN for Discrete and Continuous Layout GenerationCode1
DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented GenerationCode1
Don't Pay Attention to the Noise: Learning Self-supervised Representations of Light Curves with a Denoising Time Series TransformerCode1
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform GenerationCode1
DP-IQA: Utilizing Diffusion Prior for Blind Image Quality Assessment in the WildCode1
DETA: Denoised Task Adaptation for Few-Shot LearningCode1
DPM-OT: A New Diffusion Probabilistic Model Based on Optimal TransportCode1
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly DetectionCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
4D Facial Expression Diffusion ModelCode1
ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT DenoisingCode1
2D medical image synthesis using transformer-based denoising diffusion probabilistic modelCode1
Designing and Training of A Dual CNN for Image DenoisingCode1
AIM 2020 Challenge on Learned Image Signal Processing PipelineCode1
DS-Fusion: Artistic Typography via Discriminated and Stylized DiffusionCode1
Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image RestorationCode1
DenoSent: A Denoising Objective for Self-Supervised Sentence Representation LearningCode1
DenoMamba: A fused state-space model for low-dose CT denoisingCode1
A cross Transformer for image denoisingCode1
A Bayesian Model of Dose-Response for Cancer Drug StudiesCode1
Dual-Scale Transformer for Large-Scale Single-Pixel ImagingCode1
DVIS++: Improved Decoupled Framework for Universal Video SegmentationCode1
Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-ResolutionCode1
Artifact Restoration in Histology Images with Diffusion Probabilistic ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified