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 19011925 of 7282 papers

TitleStatusHype
Magicremover: Tuning-free Text-guided Image inpainting with Diffusion ModelsCode0
Frank-Wolfe Network: An Interpretable Deep Structure for Non-Sparse CodingCode0
Denoising-based Contractive Imitation LearningCode0
Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial DefenseCode0
Low Frequency Adversarial PerturbationCode0
LIDIA: Lightweight Learned Image Denoising with Instance AdaptationCode0
Magnetogram-to-Magnetogram: Generative Forecasting of Solar EvolutionCode0
Denoising autoencoder with modulated lateral connections learns invariant representations of natural imagesCode0
LoFi: Neural Local Fields for Scalable Image ReconstructionCode0
Low-Complexity Blind Parameter Estimation in Wireless Systems with Noisy Sparse SignalsCode0
Localized Fourier Analysis for Graph Signal ProcessingCode0
LLNet: A Deep Autoencoder Approach to Natural Low-light Image EnhancementCode0
LMD: Faster Image Reconstruction with Latent Masking DiffusionCode0
Denoising Architecture for Unsupervised Anomaly Detection in Time-SeriesCode0
Beyond Human Perception: Understanding Multi-Object World from Monocular ViewCode0
Denoising and Regularization via Exploiting the Structural Bias of Convolutional GeneratorsCode0
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold SimplificationCode0
Linear-Time Algorithm in Bayesian Image Denoising based on Gaussian Markov Random FieldCode0
LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation LearningCode0
LGC-Net: A Lightweight Gyroscope Calibration Network for Efficient Attitude EstimationCode0
Leveraging Self-supervised Denoising for Image SegmentationCode0
Lifting Layers: Analysis and ApplicationsCode0
Linking Sketch Patches by Learning Synonymous Proximity for Graphic Sketch RepresentationCode0
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor ContractionsCode0
Denoise-I2W: Mapping Images to Denoising Words for Accurate Zero-Shot Composed Image RetrievalCode0
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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