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 2251–2275 of 4856 papers

TitleStatusHype
A Self-Commissioning Edge Computing Method for Data-Driven Anomaly Detection in Power Electronic Systems—0
Anomalib: A Deep Learning Library for Anomaly Detection—0
Adversarial Activation Patching: A Framework for Detecting and Mitigating Emergent Deception in Safety-Aligned Transformers—0
Dimensionality Increment of PMU Data for Anomaly Detection in Low Observability Power Systems—0
Digraphwave: Scalable Extraction of Structural Node Embeddings via Diffusion on Directed Graphs—0
A secondary immune response based on co-evolutive populations of agents for anomaly detection and characterization—0
ASE: Anomaly Scoring Based Ensemble Learning for Imbalanced Datasets—0
Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound—0
A Scalable k-Medoids Clustering via Whale Optimization Algorithm—0
Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomalies—0
ADVENT: Attack/Anomaly Detection in VANETs—0
Acoustic Leak Detection in Water Networks—0
A Benchmark dataset for predictive maintenance—0
Fairness-aware Anomaly Detection via Fair Projection—0
A scalable framework for annotating photovoltaic cell defects in electroluminescence images—0
A Scalable Approach for Outlier Detection in Edge Streams Using Sketch-based Approximations—0
AnoGAN for Tabular Data: A Novel Approach to Anomaly Detection—0
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos—0
DiffFake: Exposing Deepfakes using Differential Anomaly Detection—0
Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability—0
A Scalable Algorithm for Anomaly Detection via Learning-Based Controlled Sensing—0
An Off-the-shelf Approach to Authorship Attribution—0
Advancing Video Anomaly Detection: A Bi-Directional Hybrid Framework for Enhanced Single- and Multi-Task Approaches—0
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation—0
Differential Anomaly Detection for Facial Images—0
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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