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 1851–1900 of 4856 papers

TitleStatusHype
Semi-Supervised Anomaly Detection for the Determination of Vehicle Hijacking Tweets—0
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks—0
Practical Anomaly Detection over Multivariate Monitoring Metrics for Online Services—0
Anomaly-Aware Semantic Segmentation via Style-Aligned OoD Augmentation—0
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly DetectionCode1
Online Transition-Based Feature Generation for Anomaly Detection in Concurrent Data Streams—0
On the Effectiveness of Log Representation for Log-based Anomaly DetectionCode1
Forensic Data Analytics for Anomaly Detection in Evolving Networks—0
Beyond Sharing: Conflict-Aware Multivariate Time Series Anomaly DetectionCode0
Detecting Financial Market Manipulation with Statistical Physics Tools—0
Interpretable Online Log Analysis Using Large Language Models with Prompt StrategiesCode1
Future Video Prediction from a Single Frame for Video Anomaly Detection—0
Searching for Novel Chemistry in Exoplanetary Atmospheres using Machine Learning for Anomaly Detection—0
ImbSAM: A Closer Look at Sharpness-Aware Minimization in Class-Imbalanced RecognitionCode1
A Graph Encoder-Decoder Network for Unsupervised Anomaly Detection—0
Digital Twin of the Radio Environment: A Novel Approach for Anomaly Detection in Wireless NetworksCode0
Survey on video anomaly detection in dynamic scenes with moving cameras—0
Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch RetrievalCode1
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection—0
ALGAN: Time Series Anomaly Detection with Adjusted-LSTM GAN—0
Out-of-Distribution Detection for Monocular Depth EstimationCode1
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation—0
A Deep Recurrent-Reinforcement Learning Method for Intelligent AutoScaling of Serverless FunctionsCode0
Deep generative models for unsupervised delamination detection using guided wavesCode0
Exploring the Potential of World Models for Anomaly Detection in Autonomous Driving—0
Sparse Binary Transformers for Multivariate Time Series Modeling—0
Multi-Class Deep SVDD: Anomaly Detection Approach in Astronomy with Distinct Inlier CategoriesCode1
Gaussian Image Anomaly Detection with Greedy Eigencomponent Selection—0
Multi-Scale Memory Comparison for Zero-/Few-Shot Anomaly Detection—0
Generative Models for Anomaly Detection and Design-Space Dimensionality Reduction in Shape Optimization—0
A Deep-Learning Method Using Auto-encoder and Generative Adversarial Network for Anomaly Detection on Ancient Stone Stele Surfaces—0
Implementing Immune Repertoire Models Using Weighted Finite State Machines—0
Detection of Anomalies in Multivariate Time Series Using Ensemble Techniques—0
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly DetectionCode1
Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA GraphCode0
Anomaly Detection in Global Financial Markets with Graph Neural Networks and Nonextensive Entropy—0
Synthetic outlier generation for anomaly detection in autonomous driving—0
Discriminative Graph-level Anomaly Detection via Dual-students-teacher ModelCode0
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain ImagesCode1
UGainS: Uncertainty Guided Anomaly Instance SegmentationCode1
Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly DetectionCode1
Achieving state-of-the-art performance in the Medical Out-of-Distribution (MOOD) challenge using plausible synthetic anomaliesCode0
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization ApproachCode1
Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach—0
Semisupervised Anomaly Detection using Support Vector Regression with Quantum Kernel—0
A Survey of Time Series Anomaly Detection Methods in the AIOps Domain—0
Patch-wise Auto-Encoder for Visual Anomaly Detection—0
PressureTransferNet: Human Attribute Guided Dynamic Ground Pressure Profile Transfer using 3D simulated Pressure Maps—0
Using Kernel SHAP XAI Method to optimize the Network Anomaly Detection Model—0
General Anomaly Detection of Underwater Gliders Validated by Large-scale Deployment Datasets—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
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
7DDADDetection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9PBASDetection AUROC99.8—Unverified
10HETMMDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4DDADDetection AUROC98.9—Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
6INP-Former ViT-B (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