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 1226–1250 of 4856 papers

TitleStatusHype
A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys—0
A Semi-Supervised Approach for Abnormal Event Prediction on Large Operational Network Time-Series Data—0
Anomalies, Representations, and Self-Supervision—0
A Benchmark dataset for predictive maintenance—0
Fairness-aware Anomaly Detection via Fair Projection—0
A self-supervised text-vision framework for automated brain abnormality detection—0
A Self-Supervised Framework for Space Object Behaviour Characterisation—0
Anomalies by Synthesis: Anomaly Detection using Generative Diffusion Models for Off-Road Navigation—0
A Self-Reasoning Framework for Anomaly Detection Using Video-Level Labels—0
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
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
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
DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions—0
Decentralized Federated Anomaly Detection in Smart Grids: A P2P Gossip Approach—0
Deep Actor-Critic Reinforcement Learning for Anomaly Detection—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
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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
4UniNetDetection AUROC99.9—Unverified
5GLASSDetection AUROC99.9—Unverified
6PBASDetection AUROC99.8—Unverified
7HETMMDetection AUROC99.8—Unverified
8INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10EfficientAD (early stopping)Detection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
5INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
6DDADDetection AUROC98.9—Unverified
7GLASSDetection AUROC98.8—Unverified
8DiffusionADDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified