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 551–600 of 4856 papers

TitleStatusHype
FLTracer: Accurate Poisoning Attack Provenance in Federated LearningCode1
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection AlgorithmsCode1
A Survey of Visual Sensory Anomaly DetectionCode1
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly DetectionCode1
Fully Convolutional Cross-Scale-Flows for Image-based Defect DetectionCode1
GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud DetectionCode1
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly DetectionCode1
Anomaly Detection in Multiplex Dynamic Networks: from Blockchain Security to Brain Disease PredictionCode1
Anomaly Detection in Multi-Agent Trajectories for Automated DrivingCode1
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
Are we certain it's anomalous?Code1
FlexFringe: Modeling Software Behavior by Learning Probabilistic AutomataCode1
ARC: A Generalist Graph Anomaly Detector with In-Context LearningCode1
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
FrAug: Frequency Domain Augmentation for Time Series ForecastingCode1
Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly DetectionCode1
Fine-grained Abnormality Prompt Learning for Zero-shot Anomaly DetectionCode1
A Principled Approach to Enriching Security-related Data for Running Processes through Statistics and Natural Language ProcessingCode1
AlerTiger: Deep Learning for AI Model Health Monitoring at LinkedInCode1
Few-shot Scene-adaptive Anomaly DetectionCode1
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data StreamCode1
FewSOME: One-Class Few Shot Anomaly Detection with Siamese NetworksCode1
Future Frame Prediction for Anomaly Detection -- A New BaselineCode1
Future Frame Prediction for Anomaly Detection – A New BaselineCode1
Applying Surface Normal Information in Drivable Area and Road Anomaly Detection for Ground Mobile RobotsCode1
An Attribute-based Method for Video Anomaly DetectionCode1
ARCADe: A Rapid Continual Anomaly DetectorCode1
AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low ToleranceCode1
Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly DetectionCode1
F-FADE: Frequency Factorization for Anomaly Detection in Edge StreamsCode1
Learning a Cross-modality Anomaly Detector for Remote Sensing ImageryCode1
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG ClassificationCode1
First-shot anomaly sound detection for machine condition monitoring: A domain generalization baselineCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative StudyCode1
Auto-Encoding Variational BayesCode1
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
GLAD: GLocalized Anomaly Detection via Human-in-the-Loop LearningCode1
Automating In-Network Machine LearningCode1
Anomaly Detection in Video Sequences: A Benchmark and Computational ModelCode1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
Few-Shot Anomaly Detection via Category-Agnostic Registration LearningCode1
Few-shot Network Anomaly Detection via Cross-network Meta-learningCode1
Anomaly Detection in Video via Self-Supervised and Multi-Task LearningCode1
Federated PCA on Grassmann Manifold for IoT Anomaly DetectionCode1
BatchNorm-based Weakly Supervised Video Anomaly DetectionCode1
AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-DecoderCode1
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine LearningCode1
Beyond Outlier Detection: Outlier Interpretation by Attention-Guided Triplet Deviation NetworkCode1
FedTADBench: Federated Time-Series Anomaly Detection BenchmarkCode1
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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