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 601–650 of 4856 papers

TitleStatusHype
Task-oriented Self-supervised Learning for Anomaly Detection in ElectroencephalographyCode1
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed RecognitionCode1
Multivariate Time Series Anomaly Detection with Few Positive SamplesCode1
Online Anomaly Detection Based On Reservoir Sampling and LOF for IoT devicesCode1
Learning Deep Feature Correspondence for Unsupervised Anomaly Detection and SegmentationCode1
Local Evaluation of Time Series Anomaly Detection AlgorithmsCode1
Multi Visual Modality Fall Detection DatasetCode1
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-raysCode1
Robustness Evaluation of Deep Unsupervised Learning Algorithms for Intrusion Detection SystemsCode1
Deep Isolation Forest for Anomaly DetectionCode1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data StreamCode1
Dual-Distribution Discrepancy for Anomaly Detection in Chest X-RaysCode1
TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study)Code1
Position Encoding Enhanced Feature Mapping for Image Anomaly DetectionCode1
Anomaly detection in surveillance videos using transformer based attention modelCode1
Fake It Till You Make It: Towards Accurate Near-Distribution Novelty DetectionCode1
Raising the Bar in Graph-level Anomaly DetectionCode1
Attention-based residual autoencoder for video anomaly detectionCode1
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier ImagesCode1
Time Series Anomaly Detection via Reinforcement Learning-Based Model SelectionCode1
Automating In-Network Machine LearningCode1
Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest RadiographsCode1
MAD: Self-Supervised Masked Anomaly Detection Task for Multivariate Time SeriesCode1
Multimodal Detection of Unknown Objects on Roads for Autonomous DrivingCode1
Anomaly Detection by Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANsCode1
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection AlgorithmsCode1
Representation Learning for Content-Sensitive Anomaly Detection in Industrial NetworksCode1
Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT HardwareCode1
LSTM-Autoencoder based Anomaly Detection for Indoor Air Quality Time Series DataCode1
Proactive Anomaly Detection for Robot Navigation with Multi-Sensor FusionCode1
LEAD1.0: A Large-scale Annotated Dataset for Energy Anomaly Detection in Commercial BuildingsCode1
AnoDFDNet: A Deep Feature Difference Network for Anomaly DetectionCode1
FlexFringe: Modeling Software Behavior by Learning Probabilistic AutomataCode1
Catching Both Gray and Black Swans: Open-set Supervised Anomaly DetectionCode1
Learning to Adapt to Unseen Abnormal Activities under Weak SupervisionCode1
Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame DetectionCode1
AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-DecoderCode1
Anomaly Detection in Emails using Machine Learning and Header InformationCode1
Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly DetectionCode1
DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing AnomaliesCode1
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly DetectionCode1
Diffusion Models for Medical Anomaly DetectionCode1
Learning Neural Set Functions Under the Optimal Subset OracleCode1
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With SupervoxelsCode1
MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasksCode1
Omni-frequency Channel-selection Representations for Unsupervised Anomaly DetectionCode1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
ICSML: Industrial Control Systems ML Framework for native inference using IEC 61131-3 codeCode1
Latent Outlier Exposure for Anomaly Detection with Contaminated DataCode1
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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