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 1526–1550 of 4856 papers

TitleStatusHype
Deep Representation Learning for Social Network Analysis—0
DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection—0
Deep Semi-Supervised Anomaly Detection for Finding Fraud in the Futures Market—0
Applications of Machine Learning to the Identification of Anomalous ER Claims—0
Anomize: Better Open Vocabulary Video Anomaly Detection—0
DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction—0
Deep Spatio-temporal Sparse Decomposition for Trend Prediction and Anomaly Detection in Cardiac Electrical Conduction—0
Deep Structured Cross-Modal Anomaly Detection—0
An Asymmetric Loss with Anomaly Detection LSTM Framework for Power Consumption Prediction—0
Applied Bayesian Structural Health Monitoring: inclinometer data anomaly detection and forecasting—0
DeepTimeAnomalyViz: A Tool for Visualizing and Post-processing Deep Learning Anomaly Detection Results for Industrial Time-Series—0
AAD: Adaptive Anomaly Detection through traffic surveillance videos—0
Deep unsupervised anomaly detection—0
Deep Unsupervised Image Anomaly Detection: An Information Theoretic Framework—0
Deep Variational Semi-Supervised Novelty Detection—0
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models—0
Deep Video Anomaly Detection: Opportunities and Challenges—0
DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions—0
Anomaly Subsequence Detection with Dynamic Local Density for Time Series—0
A Neural Network for Determination of Latent Dimensionality in Nonnegative Matrix Factorization—0
Defect Detection Approaches Based on Simulated Reference Image—0
Approaching adverse event detection utilizing transformers on clinical time-series—0
Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection—0
Defending Against Adversarial Denial-of-Service Data Poisoning Attacks—0
An Anomaly Detection System Based on Generative Classifiers for Controller Area Network—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