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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3051–3075 of 7282 papers

TitleStatusHype
Convolutional Dictionary Regularizers for Tomographic Inversion—0
Estimating User Location in Social Media with Stacked Denoising Auto-encoders—0
Functions with average smoothness: structure, algorithms, and learning—0
Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications—0
A Self-supervised Learning Method for Raman Spectroscopy based on Masked Autoencoders—0
Fundamental limits of Non-Linear Low-Rank Matrix Estimation—0
Fusing Sparsity with Deep Learning for Rotating Scatter Mask Gamma Imaging—0
Convolutional Deep Denoising Autoencoders for Radio Astronomical Images—0
FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model—0
G2L: A Global to Local Alignment Method for Unsupervised Domain Adaptive Semantic Segmentation—0
Estimating Post-OCR Denoising Complexity on Numerical Texts—0
Connecting Image Inpainting with Denoising in the Homogeneous Diffusion Setting—0
Estimating LASSO Risk and Noise Level—0
A CT Image Denoising Method Based on Projection Domain Feature—0
Grounding-Prompter: Prompting LLM with Multimodal Information for Temporal Sentence Grounding in Long Videos—0
Decision Transformers for RIS-Assisted Systems with Diffusion Model-Based Channel Acquisition—0
GAN-Based Architecture for Low-dose Computed Tomography Imaging Denoising—0
Group Sparse Coding for Image Denoising—0
GANFusion: Feed-Forward Text-to-3D with Diffusion in GAN Space—0
Decoding Diffusion: A Scalable Framework for Unsupervised Analysis of Latent Space Biases and Representations Using Natural Language Prompts—0
GSD: View-Guided Gaussian Splatting Diffusion for 3D Reconstruction—0
Guidance Free Image Editing via Explicit Conditioning—0
Heart Rate Extraction from Abdominal Audio Signals—0
Estimating High Order Gradients of the Data Distribution by Denoising—0
Estimating Fine-Grained Noise Model via Contrastive Learning—0
Show:102550
← PrevPage 123 of 292Next →
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