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 1201–1225 of 4856 papers

TitleStatusHype
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks—0
A Supervised Embedding and Clustering Anomaly Detection method for classification of Mobile Network Faults—0
A Subspace Projection Approach to Autoencoder-based Anomaly Detection—0
Anomalous State Sequence Modeling to Enhance Safety in Reinforcement Learning—0
Anomalous Sound Detection using Audio Representation with Machine ID based Contrastive Learning Pretraining—0
A Study on Unsupervised Anomaly Detection and Defect Localization using Generative Model in Ultrasonic Non-Destructive Testing—0
Adversarial Learning-Based On-Line Anomaly Monitoring for Assured Autonomy—0
A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods—0
Anomalous Sound Detection Based on Machine Activity Detection—0
AstroM^3: A self-supervised multimodal model for astronomy—0
Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection—0
ASTD Patterns for Integrated Continuous Anomaly Detection In Data Logs—0
A Stacked Autoencoder Neural Network based Automated Feature Extraction Method for Anomaly detection in On-line Condition Monitoring—0
Dance With Self-Attention: A New Look of Conditional Random Fields on Anomaly Detection in Videos—0
AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection—0
AssistPDA: An Online Video Surveillance Assistant for Video Anomaly Prediction, Detection, and Analysis—0
FusionNet: Incorporating Shape and Texture for Abnormality Detection in 3D Abdominal CT Scans—0
Assessing workflow impact and clinical utility of AI-assisted brain aneurysm detection: a multi-reader study—0
A Bi-LSTM Autoencoder Framework for Anomaly Detection -- A Case Study of a Wind Power Dataset—0
Few-shot 1/a Anomalies Feedback : Damage Vision Mining Opportunity and Embedding Feature Imbalance—0
DAS3D: Dual-modality Anomaly Synthesis for 3D Anomaly Detection—0
Data-Agnostic Face Image Synthesis Detection Using Bayesian CNNs—0
Assessing Cyclostationary Malware Detection via Feature Selection and Classification—0
A spectral-spatial fusion anomaly detection method for hyperspectral imagery—0
Anomalous Example Detection in Deep Learning: A Survey—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