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 16011625 of 4856 papers

TitleStatusHype
Enhancing Fairness in Unsupervised Graph Anomaly Detection through DisentanglementCode0
Enhancing Robustness of On-line Learning Models on Highly Noisy DataCode0
Enhancing Wrist Fracture Detection with YOLOCode0
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly DetectionCode0
ENCODE: Encoding NetFlows for Network Anomaly DetectionCode0
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-ADCode0
Enhanced anomaly detection in well log data through the application of ensemble GANsCode0
Bump Hunting in Latent SpaceCode0
AssemAI: Interpretable Image-Based Anomaly Detection for Manufacturing PipelinesCode0
Building and Interpreting Deep Similarity ModelsCode0
Anomaly Detection in High Dimensional DataCode0
Eloss in the way: A Sensitive Input Quality Metrics for Intelligent DrivingCode0
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of AugmentationCode0
Ensemble Clustering for Graphs: Comparisons and ApplicationsCode0
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality DetectionCode0
BRUNO: A Deep Recurrent Model for Exchangeable DataCode0
AIDA: Analytic Isolation and Distance-based Anomaly Detection AlgorithmCode0
Early-Stage Anomaly Detection: A Study of Model Performance on Complete vs. Partial FlowsCode0
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health EpisodesCode0
E-ABIN: an Explainable module for Anomaly detection in BIological NetworksCode0
Bridging 3D Anomaly Localization and Repair via High-Quality Continuous Geometric RepresentationCode0
Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment PerspectiveCode0
Action Sequence Augmentation for Early Graph-based Anomaly DetectionCode0
Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly DetectionCode0
Effective and Efficient Representation Learning for Flight TrajectoriesCode0
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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
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (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