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 926950 of 7282 papers

TitleStatusHype
Information-Theoretic DiffusionCode1
Adaptive Unfolding Total Variation Network for Low-Light Image EnhancementCode1
DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative RefinementCode1
Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-raysCode1
Intermediate Layer Optimization for Inverse Problems using Deep Generative ModelsCode1
Blind ECG Restoration by Operational Cycle-GANsCode1
3D Detection and Characterisation of ALMA Sources through Deep LearningCode1
Diffusive Gibbs SamplingCode1
Invariance Matters: Empowering Social Recommendation via Graph Invariant LearningCode1
1st Place Solution for the 5th LSVOS Challenge: Video Instance SegmentationCode1
E-MLB: Multilevel Benchmark for Event-Based Camera DenoisingCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
Invertible Denoising Network: A Light Solution for Real Noise RemovalCode1
Civil Rephrases Of Toxic Texts With Self-Supervised TransformersCode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image RestorationCode1
Iterative Gaussianization: from ICA to Random RotationsCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
DFormer: Diffusion-guided Transformer for Universal Image SegmentationCode1
DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein TracesCode1
Are Diffusion Models Vision-And-Language Reasoners?Code1
Joint Low Dose CT Denoising And Kidney SegmentationCode1
Joint-Modal Label Denoising for Weakly-Supervised Audio-Visual Video ParsingCode1
Joint self-supervised blind denoising and noise estimationCode1
Adversarial Distortion Learning for Medical Image DenoisingCode1
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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