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

Showing 676700 of 4856 papers

TitleStatusHype
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly DetectionCode1
Learning Graph Neural Networks for Multivariate Time Series Anomaly DetectionCode1
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing FlowsCode1
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the BoundaryCode1
Sensing Anomalies as Potential Hazards: Datasets and BenchmarksCode1
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future ChallengesCode1
Practical Galaxy Morphology Tools from Deep Supervised Representation LearningCode1
Generalized Out-of-Distribution Detection: A SurveyCode1
Synthetic Temporal Anomaly Guided End-to-End Video Anomaly DetectionCode1
Learning Not to Reconstruct AnomaliesCode1
Anomaly Detection in Multi-Agent Trajectories for Automated DrivingCode1
Fully Convolutional Cross-Scale-Flows for Image-based Defect DetectionCode1
Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and LocalizationCode1
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time SeriesCode1
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security ApplicationsCode1
Merlion: A Machine Learning Library for Time SeriesCode1
Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRICode1
Towards a Rigorous Evaluation of Time-series Anomaly DetectionCode1
PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data StreamsCode1
Optimal Reservoir Operations using Long Short-Term Memory NetworkCode1
Self-supervised Pseudo Multi-class Pre-training for Unsupervised Anomaly Detection and Segmentation in Medical ImagesCode1
Deep Dual Support Vector Data Description for Anomaly Detection on Attributed NetworksCode1
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set FrameworkCode1
Normal Learning in Videos with Attention Prototype NetworkCode1
Generative and Contrastive Self-Supervised Learning for Graph Anomaly DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
7DDADDetection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9PBASDetection AUROC99.8Unverified
10HETMMDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4DDADDetection AUROC98.9Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
6INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified