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 1451–1475 of 7282 papers

TitleStatusHype
Stochastic Deep Restoration Priors for Imaging Inverse Problems—0
Denoising with a Joint-Embedding Predictive Architecture—0
Discrete Copula Diffusion—0
Tuning Frequency Bias of State Space Models—0
FabricDiffusion: High-Fidelity Texture Transfer for 3D Garments Generation from In-The-Wild Clothing Images—0
Edge-preserving noise for diffusion modelsCode1
HarmoniCa: Harmonizing Training and Inference for Better Feature Caching in Diffusion Transformer AccelerationCode1
A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding OptimizationCode1
LaDTalk: Latent Denoising for Synthesizing Talking Head Videos with High Frequency Details—0
Generative Precipitation Downscaling using Score-based Diffusion with Wasserstein Regularization—0
Denoising VAE as an Explainable Feature Reduction and Diagnostic Pipeline for Autism Based on Resting state fMRI—0
(Almost) Smooth Sailing: Towards Numerical Stability of Neural Networks Through Differentiable Regularization of the Condition NumberCode0
Volumetric Conditional Score-based Residual Diffusion Model for PET/MR DenoisingCode1
Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamicsCode0
FreeMask: Rethinking the Importance of Attention Masks for Zero-Shot Video Editing—0
Enhancing GANs with Contrastive Learning-Based Multistage Progressive Finetuning SNN and RL-Based External Optimization—0
COLLAGE: Collaborative Human-Agent Interaction Generation using Hierarchical Latent Diffusion and Language Models—0
Fine-Tuning Hybrid Physics-Informed Neural Networks for Vehicle Dynamics Model Estimation—0
MCDDPM: Multichannel Conditional Denoising Diffusion Model for Unsupervised Anomaly Detection in Brain MRICode1
SemiDDM-Weather: A Semi-supervised Learning Framework for All-in-one Adverse Weather RemovalCode0
Vision-Language Models are Strong Noisy Label DetectorsCode1
Efficient Semantic Diffusion Architectures for Model Training on Synthetic EchocardiogramsCode0
Conditional Image Synthesis with Diffusion Models: A SurveyCode2
A Proximal Modified Quasi-Newton Method for Nonsmooth Regularized Optimization—0
Efficient Noise Mitigation for Enhancing Inference Accuracy in DNNs on Mixed-Signal Accelerators—0
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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