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 1351–1375 of 7282 papers

TitleStatusHype
Denoise and Contrast for Category Agnostic Shape CompletionCode1
Civil Rephrases Of Toxic Texts With Self-Supervised TransformersCode1
A CNN-Based Blind Denoising Method for Endoscopic ImagesCode1
DNTextSpotter: Arbitrary-Shaped Scene Text Spotting via Improved Denoising TrainingCode1
Convolutional Proximal Neural Networks and Plug-and-Play AlgorithmsCode1
Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language ModelsCode1
Domain Generalization for Object Recognition with Multi-task AutoencodersCode1
DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented GenerationCode1
Action-Conditioned 3D Human Motion Synthesis with Transformer VAECode1
Don't Pay Attention to the Noise: Learning Self-supervised Representations of Light Curves with a Denoising Time Series TransformerCode1
DoseDiff: Distance-aware Diffusion Model for Dose Prediction in RadiotherapyCode1
Intermediate Layer Optimization for Inverse Problems using Deep Generative ModelsCode1
Interpreting Low-level Vision Models with Causal Effect MapsCode1
Joint multi-dimensional dynamic attention and transformer for general image restorationCode1
DP-IQA: Utilizing Diffusion Prior for Blind Image Quality Assessment in the WildCode1
DPMesh: Exploiting Diffusion Prior for Occluded Human Mesh RecoveryCode1
Learning Enriched Features for Real Image Restoration and EnhancementCode1
Input Perturbation Reduces Exposure Bias in Diffusion ModelsCode1
-Diff: Infinite Resolution Diffusion with Subsampled Mollified StatesCode1
Input Similarity from the Neural Network PerspectiveCode1
Decoder Denoising Pretraining for Semantic SegmentationCode1
Multimodal Knowledge ExpansionCode1
CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-ThoughtCode1
Score-based denoising for atomic structure identificationCode1
InstructG2I: Synthesizing Images from Multimodal Attributed GraphsCode1
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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