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
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos0
Anomaly Detection and Localization for Speech Deepfakes via Feature Pyramid Matching0
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space ModelCode0
Anomize: Better Open Vocabulary Video Anomaly Detection0
Assessing workflow impact and clinical utility of AI-assisted brain aneurysm detection: a multi-reader study0
Bayesian generative models can flag performance loss, bias, and out-of-distribution image content0
TRACE: Time SeRies PArameter EffiCient FinE-tuning0
CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series0
Multivariate Time Series Anomaly Detection in Industry 5.00
A multi-model approach using XAI and anomaly detection to predict asteroid hazards0
Automated Processing of eXplainable Artificial Intelligence Outputs in Deep Learning Models for Fault Diagnostics of Large Infrastructures0
FetalFlex: Anatomy-Guided Diffusion Model for Flexible Control on Fetal Ultrasound Image Synthesis0
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging InfrastructureCode0
Robust Distribution Alignment for Industrial Anomaly Detection under Distribution Shift0
LogLLaMA: Transformer-based log anomaly detection with LLaMA0
Reducing Communication Overhead in Federated Learning for Network Anomaly Detection with Adaptive Client Selection0
Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly DetectionCode0
EIAD: Explainable Industrial Anomaly Detection Via Multi-Modal Large Language Models0
U2AD: Uncertainty-based Unsupervised Anomaly Detection Framework for Detecting T2 Hyperintensity in MRI Spinal CordCode0
Enforcing Cybersecurity Constraints for LLM-driven Robot Agents for Online Transactions0
MFP-CLIP: Exploring the Efficacy of Multi-Form Prompts for Zero-Shot Industrial Anomaly Detection0
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly DetectionCode0
Unsupervised Graph Anomaly Detection via Multi-Hypersphere Heterophilic Graph LearningCode0
Adaptive Fault Tolerance Mechanisms of Large Language Models in Cloud Computing Environments0
Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection0
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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