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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1851–1875 of 4856 papers

TitleStatusHype
Activity-Guided Industrial Anomalous Sound Detection against Interferences—0
Abnormal Event Detection In Videos Using Deep Embedding—0
A Unified Simulation Framework for Visual and Behavioral Fidelity in Crowd Analysis—0
Anomaly Detection Based on Selection and Weighting in Latent Space—0
A Unified Off-Policy Evaluation Approach for General Value Function—0
Anomaly Detection Based on Multiple-Hypothesis Autoencoder—0
A Unified Latent Schrodinger Bridge Diffusion Model for Unsupervised Anomaly Detection and Localization—0
Anomaly Detection Based on Isolation Mechanisms: A Survey—0
Enhanced Cyber-Physical Security through Deep Learning Techniques—0
Enhanced Anomaly Detection in Automotive Systems Using SAAD: Statistical Aggregated Anomaly Detection—0
A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection—0
Anomaly Detection Based on Indicators Aggregation—0
Active Rule Mining for Multivariate Anomaly Detection in Radio Access Networks—0
Engineering Risk-Aware, Security-by-Design Frameworks for Assurance of Large-Scale Autonomous AI Models—0
EnGAN: Latent Space MCMC and Maximum Entropy Generators for Energy-based Models—0
Augment to Detect Anomalies with Continuous Labelling—0
Enforcing Cybersecurity Constraints for LLM-driven Robot Agents for Online Transactions—0
Augmentation based unsupervised domain adaptation—0
Anomaly Detection Based on Generalized Gaussian Distribution approach for Ultra-Wideband (UWB) Indoor Positioning System—0
Energy-Efficient Respiratory Anomaly Detection in Premature Newborn Infants—0
Energy-Efficient Classification for Anomaly Detection: The Wireless Channel as a Helper—0
Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset—0
Auditing Keyword Queries Over Text Documents—0
Energy-based Models for Video Anomaly Detection—0
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach—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
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
7DDADDetection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9PBASDetection AUROC99.8—Unverified
10HETMMDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4DDADDetection AUROC98.9—Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
6INP-Former ViT-B (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