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 1776–1800 of 7282 papers

TitleStatusHype
Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis—0
Novel Hybrid Integrated Pix2Pix and WGAN Model with Gradient Penalty for Binary Images DenoisingCode0
Magnetogram-to-Magnetogram: Generative Forecasting of Solar EvolutionCode0
Contrastive Sequential-Diffusion Learning: Non-linear and Multi-Scene Instructional Video SynthesisCode0
An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited DataCode0
2D Neural Fields with Learned Discontinuities—0
Integrating Amortized Inference with Diffusion Models for Learning Clean Distribution from Corrupted Images—0
Optical Diffusion Models for Image Generation—0
IDOL: Unified Dual-Modal Latent Diffusion for Human-Centric Joint Video-Depth GenerationCode2
Backdoor Attacks against Image-to-Image Networks—0
Physics-Inspired Generative Models in Medical Imaging: A Review—0
Temporal Residual Guided Diffusion Framework for Event-Driven Video Reconstruction—0
Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKVCode2
Pre-training with Fractional Denoising to Enhance Molecular Property Prediction—0
Noise Calibration: Plug-and-play Content-Preserving Video Enhancement using Pre-trained Video Diffusion ModelsCode2
DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image SegmentationCode2
ECG Signal Denoising Using Multi-scale Patch Embedding and Transformers—0
Unsupervised Anomaly Detection Using Diffusion Trend Analysis—0
Fast and Robust Phase Retrieval via Deep Expectation-Consistent ApproximationCode0
Beyond Image Prior: Embedding Noise Prior into Conditional Denoising TransformerCode1
FD-SOS: Vision-Language Open-Set Detectors for Bone Fenestration and Dehiscence Detection from Intraoral ImagesCode1
Region Attention Transformer for Medical Image RestorationCode1
Enhancing Few-Shot Stock Trend Prediction with Large Language Models—0
Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive TrainingCode1
DG-PIC: Domain Generalized Point-In-Context Learning for Point Cloud Understanding—0
Show:102550
← PrevPage 72 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