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

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Showing 651–700 of 4856 papers

TitleStatusHype
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly DetectionCode1
A Survey of Visual Sensory Anomaly DetectionCode1
Detecting Anomalies within Time Series using Local Neural TransformationsCode1
Time Series Anomaly Detection by Cumulative Radon FeaturesCode1
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine LearningCode1
StRegA: Unsupervised Anomaly Detection in Brain MRIs using a Compact Context-encoding Variational AutoencoderCode1
Time-Series Anomaly Detection with Implicit Neural RepresentationCode1
The Effects of Reward Misspecification: Mapping and Mitigating Misaligned ModelsCode1
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution FunctionsCode1
Dual Task Learning by Leveraging Both Dense Correspondence and Mis-Correspondence for Robust Change Detection With Imperfect MatchesCode1
Continual Learning for Unsupervised Anomaly Detection in Continuous Auditing of Financial Accounting DataCode1
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly TypesCode1
Deep Graph-level Anomaly Detection by Glocal Knowledge DistillationCode1
The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and LocalizationCode1
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural NetworksCode1
PixMix: Dreamlike Pictures Comprehensively Improve Safety MeasuresCode1
Transformaly -- Two (Feature Spaces) Are Better Than OneCode1
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly DetectionCode1
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent AutoencodersCode1
Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge DistillationCode1
SQUID: Deep Feature In-Painting for Unsupervised Anomaly DetectionCode1
SLA^2P: Self-supervised Anomaly Detection with Adversarial PerturbationCode1
Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving ScenesCode1
Self-Supervised Predictive Convolutional Attentive Block for Anomaly DetectionCode1
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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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