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 16511675 of 7282 papers

TitleStatusHype
DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging LoadCode1
Deep Random Projector: Accelerated Deep Image PriorCode1
Deep Mesh Prior: Unsupervised Mesh Restoration using Graph Convolutional NetworksCode1
A zero-inflated gamma model for deconvolved calcium imaging tracesCode1
RGB-Event ISP: The Dataset and BenchmarkCode1
Empowering Diffusion Models on the Embedding Space for Text GenerationCode1
DiffPO: A causal diffusion model for learning distributions of potential outcomesCode1
RMDM: Radio Map Diffusion Model with Physics InformedCode1
Backpropagation-Friendly EigendecompositionCode1
RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy ResponseCode1
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time StepsCode1
DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraintsCode1
Diff-UNet: A Diffusion Embedded Network for Volumetric SegmentationCode1
DifFIQA: Face Image Quality Assessment Using Denoising Diffusion Probabilistic ModelsCode1
RU-Net: Regularized Unrolling Network for Scene Graph GenerationCode1
S^2DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph CompletionCode1
Accelerated MRI with Un-trained Neural NetworksCode1
A deep network for sinogram and CT image reconstructionCode1
SAR2SAR: a semi-supervised despeckling algorithm for SAR imagesCode1
SAR Despeckling using a Denoising Diffusion Probabilistic ModelCode1
Diff-IP2D: Diffusion-Based Hand-Object Interaction Prediction on Egocentric VideosCode1
Accurate Image Restoration with Attention Retractable TransformerCode1
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super ResolutionCode1
Scientific Image Restoration AnywhereCode1
Can LLMs be Good Graph Judge for Knowledge Graph Construction?Code1
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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