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 876900 of 7282 papers

TitleStatusHype
Guided Diffusion Model for Adversarial PurificationCode1
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIsCode1
HarmoniCa: Harmonizing Training and Inference for Better Feature Caching in Diffusion Transformer AccelerationCode1
Adversarial purification with Score-based generative modelsCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
A Mixture-Based Framework for Guiding Diffusion ModelsCode1
Beyond Image Prior: Embedding Noise Prior into Conditional Denoising TransformerCode1
Designing and Training of A Dual CNN for Image DenoisingCode1
A Continuous Time Framework for Discrete Denoising ModelsCode1
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly DetectionCode1
Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image RestorationCode1
Diff-IP2D: Diffusion-Based Hand-Object Interaction Prediction on Egocentric VideosCode1
HiPrompt: Tuning-free Higher-Resolution Generation with Hierarchical MLLM PromptsCode1
Beyond Surface Statistics: Scene Representations in a Latent Diffusion ModelCode1
Diffusion Posterior Proximal Sampling for Image RestorationCode1
Efficient Diffusion Training via Min-SNR Weighting StrategyCode1
Homotopic Gradients of Generative Density Priors for MR Image ReconstructionCode1
How Framelets Enhance Graph Neural NetworksCode1
Denoising Relation Extraction from Document-level Distant SupervisionCode1
Denoising Point Clouds in Latent Space via Graph Convolution and Invertible Neural NetworkCode1
Can LLMs be Good Graph Judge for Knowledge Graph Construction?Code1
Hybrid Spectral Denoising Transformer with Guided AttentionCode1
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising PackageCode1
Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural NetworksCode1
Denoising Task Routing for Diffusion 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