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 801–825 of 7282 papers

TitleStatusHype
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based PenaltiesCode1
Denoising diffusion-based MRI to CT image translation enables automated spinal segmentationCode1
Denoising diffusion models for out-of-distribution detectionCode1
Denoising Diffusion Models for 3D Healthy Brain Tissue InpaintingCode1
Controlling Latent Diffusion Using Latent CLIPCode1
Efficient View Synthesis and 3D-based Multi-Frame Denoising with Multiplane Feature RepresentationsCode1
4D Facial Expression Diffusion ModelCode1
ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT DenoisingCode1
A Light and Tuning-free Method for Simulating Camera Motion in Video GenerationCode1
Denoising Diffusion Probabilistic Models for Generation of Realistic Fully-Annotated Microscopy Image Data SetsCode1
EGC: Image Generation and Classification via a Diffusion Energy-Based ModelCode1
Autoregressive Diffusion Model for Graph GenerationCode1
TTS-Portuguese Corpus: a corpus for speech synthesis in Brazilian PortugueseCode1
Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracyCode1
Contrastive Denoising Score for Text-guided Latent Diffusion Image EditingCode1
Efficient Diffusion Transformer with Step-wise Dynamic Attention MediatorsCode1
Aligning Few-Step Diffusion Models with Dense Reward Difference LearningCode1
A Variational Perspective on Solving Inverse Problems with Diffusion ModelsCode1
Adaptive Diffusion Terrain Generator for Autonomous Uneven Terrain NavigationCode1
Diffiner: A Versatile Diffusion-based Generative Refiner for Speech EnhancementCode1
Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual PerceptionCode1
Denoising IMU Gyroscopes with Deep Learning for Open-Loop Attitude EstimationCode1
Denoising MCMC for Accelerating Diffusion-Based Generative ModelsCode1
Denoising Multi-Source Weak Supervision for Neural Text ClassificationCode1
EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit 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