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 3251–3275 of 7282 papers

TitleStatusHype
DiffProsody: Diffusion-based Latent Prosody Generation for Expressive Speech Synthesis with Prosody Conditional Adversarial TrainingCode1
Towards General Low-Light Raw Noise Synthesis and ModelingCode1
Universal Adversarial Defense in Remote Sensing Based on Pre-trained Denoising Diffusion ModelsCode1
Contrastive Conditional Latent Diffusion for Audio-visual SegmentationCode0
Random Sub-Samples Generation for Self-Supervised Real Image DenoisingCode1
DiffPose: SpatioTemporal Diffusion Model for Video-Based Human Pose Estimation—0
Crystal Structure Prediction by Joint Equivariant DiffusionCode1
A Novel DDPM-based Ensemble Approach for Energy Theft Detection in Smart Grids—0
Fusing Sparsity with Deep Learning for Rotating Scatter Mask Gamma Imaging—0
RGB-D-Fusion: Image Conditioned Depth Diffusion of Humanoid SubjectsCode0
Ultrasound Image Reconstruction with Denoising Diffusion Restoration ModelsCode1
AbDiffuser: Full-Atom Generation of in vitro Functioning Antibodies—0
Exploring Format Consistency for Instruction TuningCode0
Generative AI for Medical Imaging: extending the MONAI FrameworkCode2
TEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis—0
Spatial-Frequency U-Net for Denoising Diffusion Probabilistic Models—0
Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEGCode1
Pre-Training with Diffusion models for Dental Radiography segmentation—0
Understanding and Tackling Scattering and Reflective Flare for Mobile Camera Systems—0
How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data?Code0
Artifact Restoration in Histology Images with Diffusion Probabilistic ModelsCode1
Attenuation of Seismic Random Noise With Unknown Distribution: A Gaussianization FrameworkCode0
Gradient-based adaptive wavelet de-noising method for photoacoustic imaging in vivo—0
Denoising Variational Graph of Graphs Auto-Encoder for Predicting Structured Entity InteractionsCode0
Interpolating between Images with Diffusion ModelsCode1
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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