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 326–350 of 4856 papers

TitleStatusHype
Detecting Anomalies within Time Series using Local Neural TransformationsCode1
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language ModelsCode1
AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and LocalizationCode1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
A Principled Approach to Enriching Security-related Data for Running Processes through Statistics and Natural Language ProcessingCode1
A Multi-Scale Decomposition MLP-Mixer for Time Series AnalysisCode1
Applying Surface Normal Information in Drivable Area and Road Anomaly Detection for Ground Mobile RobotsCode1
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly DetectionCode1
GLAD: Content-aware Dynamic Graphs For Log Anomaly DetectionCode1
ARC: A Generalist Graph Anomaly Detector with In-Context LearningCode1
Diffusion Models with Implicit Guidance for Medical Anomaly DetectionCode1
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly DetectionCode1
Anomaly localization by modeling perceptual featuresCode1
DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density EstimationCode1
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection AlgorithmsCode1
Does Graph Distillation See Like Vision Dataset Counterpart?Code1
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly DetectionCode1
Are we certain it's anomalous?Code1
A Survey of Visual Sensory Anomaly DetectionCode1
DRAEM - A Discriminatively Trained Reconstruction Embedding for Surface Anomaly DetectionCode1
Deep Structured Energy Based Models for Anomaly DetectionCode1
DSR -- A dual subspace re-projection network for surface anomaly detectionCode1
Deep SetsCode1
DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 PandemicCode1
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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
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (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