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 14511475 of 7282 papers

TitleStatusHype
Data-Driven Denoising of Stationary Accelerometer SignalsCode1
Diffusion Model for Dense MatchingCode1
DiffProsody: Diffusion-based Latent Prosody Generation for Expressive Speech Synthesis with Prosody Conditional Adversarial TrainingCode1
Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEGCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic ModelsCode1
Data-Centric Learning from Unlabeled Graphs with Diffusion ModelCode1
D3A-TS: Denoising-Driven Data Augmentation in Time SeriesCode1
DiffDA: a Diffusion Model for Weather-scale Data AssimilationCode1
D3RM: A Discrete Denoising Diffusion Refinement Model for Piano TranscriptionCode1
D4AM: A General Denoising Framework for Downstream Acoustic ModelsCode1
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising DiffusionCode1
D^4-VTON: Dynamic Semantics Disentangling for Differential Diffusion based Virtual Try-OnCode1
DAEMA: Denoising Autoencoder with Mask AttentionCode1
DiffFashion: Reference-based Fashion Design with Structure-aware Transfer by Diffusion ModelsCode1
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic ModelsCode1
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform GenerationCode1
DALE: Generative Data Augmentation for Low-Resource Legal NLPCode1
MIDA: Multiple Imputation using Denoising AutoencodersCode1
MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule GenerationCode1
A Cheaper and Better Diffusion Language Model with Soft-Masked NoiseCode1
DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion ModelCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
DFormer: Diffusion-guided Transformer for Universal Image SegmentationCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
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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