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 41764200 of 4856 papers

TitleStatusHype
Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time seriesCode0
AndroShield: Automated Android Applications Vulnerability Detection, a Hybrid Static and Dynamic Analysis ApproachCode0
MAD-EN: Microarchitectural Attack Detection through System-wide Energy ConsumptionCode0
MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial NetworksCode0
Subtractive Aggregation for Attributed Network Anomaly DetectionCode0
Isconna: Streaming Anomaly Detection with Frequency and PatternsCode0
Unsupervised crack detection on complex stone masonry surfacesCode0
Is AUC the best measure for practical comparison of anomaly detectors?Code0
Combining AI and AM - Improving Approximate Matching through Transformer NetworksCode0
Is Your Anomaly Detector Ready for Change? Adapting AIOps Solutions to the Real WorldCode0
IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical DomainCode0
Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and DestroyerCode0
Retrieval Augmented Deep Anomaly Detection for Tabular DataCode0
Inverting Adversarially Robust Networks for Image SynthesisCode0
Discovering Antagonists in Networks of Systems: Robot DeploymentCode0
Invertible Neural Networks for Graph PredictionCode0
CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densitiesCode0
Attribute Restoration Framework for Anomaly DetectionCode0
DINAMO: Dynamic and INterpretable Anomaly MOnitoring for Large-Scale Particle Physics ExperimentsCode0
ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous FeaturesCode0
TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformersCode0
MAPL: Memory Augmentation and Pseudo-Labeling for Semi-Supervised Anomaly DetectionCode0
Mapper Comparison with Wasserstein MetricsCode0
Margin-Aware Intra-Class Novelty Identification for Medical ImagesCode0
Digital Twin of the Radio Environment: A Novel Approach for Anomaly Detection in Wireless NetworksCode0
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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