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 1476–1500 of 7282 papers

TitleStatusHype
Diff-IP2D: Diffusion-Based Hand-Object Interaction Prediction on Egocentric VideosCode1
MODNet: Multi-offset Point Cloud Denoising Network Customized for Multi-scale PatchesCode1
ModWaveMLP: MLP-Based Mode Decomposition and Wavelet Denoising Model to Defeat Complex Structures in Traffic ForecastingCode1
Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEGCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion ModelsCode1
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image RestorationCode1
DifFIQA: Face Image Quality Assessment Using Denoising Diffusion Probabilistic ModelsCode1
DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion ModelCode1
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic ModelsCode1
A Cheaper and Better Diffusion Language Model with Soft-Masked NoiseCode1
DiffDA: a Diffusion Model for Weather-scale Data AssimilationCode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
Data-Driven Denoising of Stationary Accelerometer SignalsCode1
Multi-dimensional Visual Prompt Enhanced Image Restoration via Mamba-Transformer AggregationCode1
Multilingual Denoising Pre-training for Neural Machine TranslationCode1
DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein TracesCode1
Multimodal Knowledge ExpansionCode1
Multimodal LLM-Guided Semantic Correction in Text-to-Image DiffusionCode1
Deep Plug-and-Play Prior for Hyperspectral Image RestorationCode1
Multi-stage image denoising with the wavelet transformCode1
DFormer: Diffusion-guided Transformer for Universal Image SegmentationCode1
MultiSV: Dataset for Far-Field Multi-Channel Speaker VerificationCode1
Multivector Neurons: Better and Faster O(n)-Equivariant Clifford Graph Neural NetworksCode1
Certified Robustness for Large Language Models with Self-DenoisingCode1
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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