SOTAVerified

Anomaly Detection

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3801–3825 of 4856 papers

TitleStatusHype
Attention Guided Anomaly Localization in Images—0
Attention-Guided Perturbation for Unsupervised Image Anomaly Detection—0
Attention Map-guided Two-stage Anomaly Detection using Hard Augmentation—0
Attention Modules Improve Modern Image-Level Anomaly Detection: A DifferNet Case Study—0
Attention to Patterns is all you need for Insider threat detection—0
Attire-Based Anomaly Detection in Restricted Areas Using YOLOv8 for Enhanced CCTV Security—0
A Tube-and-Droplet-based Approach for Representing and Analyzing Motion Trajectories—0
A Typology of Data Anomalies—0
Audio-based Anomaly Detection in Industrial Machines Using Deep One-Class Support Vector Data Description—0
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing—0
Auditing Keyword Queries Over Text Documents—0
Augmentation based unsupervised domain adaptation—0
Augment to Detect Anomalies with Continuous Labelling—0
A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection—0
A Unified Latent Schrodinger Bridge Diffusion Model for Unsupervised Anomaly Detection and Localization—0
A Unified Off-Policy Evaluation Approach for General Value Function—0
A Unified Simulation Framework for Visual and Behavioral Fidelity in Crowd Analysis—0
A Unifying Review of Deep and Shallow Anomaly Detection—0
Autoencoder based Anomaly Detection and Explained Fault Localization in Industrial Cooling Systems—0
Autoencoder-based Anomaly Detection in Streaming Data with Incremental Learning and Concept Drift Adaptation—0
Autoencoder-based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter—0
Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines—0
Autoencoder-Based Detection of Anomalous Stokes V Spectra in the Flare-Producing Active Region 13663 Using Hinode/SP Observations—0
Autoencoder-based Online Data Quality Monitoring for the CMS Electromagnetic Calorimeter—0
AutoEncoder Convolutional Neural Network for Pneumonia Detection—0
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All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified