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 1501–1525 of 7282 papers

TitleStatusHype
DCT2net: an interpretable shallow CNN for image denoisingCode1
(Certified!!) Adversarial Robustness for Free!Code1
3DInvNet: A Deep Learning-Based 3D Ground-Penetrating Radar Data InversionCode1
Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEGCode1
CERL: A Unified Optimization Framework for Light Enhancement with Realistic NoiseCode1
Neural Transfer Learning for Repairing Security Vulnerabilities in C CodeCode1
DDIM sampling for Generative AIBIM, a faster intelligent structural design frameworkCode1
DDM^2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion ModelsCode1
NIR-Assisted Image Denoising: A Selective Fusion Approach and A Real-World Benchmark DatasetCode1
NM-FlowGAN: Modeling sRGB Noise without Paired Images using a Hybrid Approach of Normalizing Flows and GANCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraintsCode1
Noise2Noise: Learning Image Restoration without Clean DataCode1
Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised LearningCode1
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform GenerationCode1
Noise2Self: Blind Denoising by Self-SupervisionCode1
Noise2Void - Learning Denoising from Single Noisy ImagesCode1
CDLNet: Robust and Interpretable Denoising Through Deep Convolutional Dictionary LearningCode1
DDT: Dual-branch Deformable Transformer for Image DenoisingCode1
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-ExpertsCode1
Noise-Injected Spiking Graph Convolution for Energy-Efficient 3D Point Cloud DenoisingCode1
CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and DemosaicingCode1
ACDiT: Interpolating Autoregressive Conditional Modeling and Diffusion TransformerCode1
Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image RestorationCode1
CCSPNet-Joint: Efficient Joint Training Method for Traffic Sign Detection Under Extreme ConditionsCode1
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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