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 11761200 of 4856 papers

TitleStatusHype
Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly DetectionCode0
Heartbeat Anomaly Detection using Adversarial OversamplingCode0
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural NetworksCode0
High-dimensional and Permutation Invariant Anomaly DetectionCode0
An Unsupervised Framework for Anomaly Detection in a Water Treatment System.Code0
Hallucinated Heartbeats: Anomaly-Aware Remote Pulse EstimationCode0
HACD: Harnessing Attribute Semantics and Mesoscopic Structure for Community DetectionCode0
Hack Me If You Can: Aggregating AutoEncoders for Countering Persistent Access Threats Within Highly Imbalanced DataCode0
Achieving state-of-the-art performance in the Medical Out-of-Distribution (MOOD) challenge using plausible synthetic anomaliesCode0
AndroShield: Automated Android Applications Vulnerability Detection, a Hybrid Static and Dynamic Analysis ApproachCode0
ADKGD: Anomaly Detection in Knowledge Graphs with Dual-Channel TrainingCode0
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula ProcessesCode0
Identifying the Defective: Detecting Damaged Grains for Cereal Appearance InspectionCode0
An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videosCode0
A Novel Self-Supervised Learning-Based Anomaly Node Detection Method Based on an Autoencoder in Wireless Sensor NetworksCode0
Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing ValuesCode0
A Novel Multi-Stage Approach for Hierarchical Intrusion DetectionCode0
A Novel Center-based Deep Contrastive Metric Learning Method for the Detection of Polymicrogyria in Pediatric Brain MRICode0
Graph Laplacian for Image Anomaly DetectionCode0
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly DetectionCode0
An Autoencoder Architecture for L-band Passive Microwave Retrieval of Landscape Freeze-Thaw CycleCode0
Graph Embedded Pose Clustering for Anomaly DetectionCode0
Good Practices and A Strong Baseline for Traffic Anomaly DetectionCode0
GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through GradientCode0
Graph Fairing Convolutional Networks for Anomaly DetectionCode0
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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