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 3151–3200 of 4856 papers

TitleStatusHype
Spatial-Temporal Anomaly Detection for Sensor Attacks in Autonomous Vehicles—0
Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies, and Opportunities—0
Detecting Anomalies in Dynamic Graphs via Memory enhanced Normality—0
Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter—0
Spatio-Temporal-based Context Fusion for Video Anomaly Detection—0
Spatio-Temporal Correlation Analysis of Online Monitoring Data for Anomaly Detection and Location in Distribution Networks—0
Spatio-temporal predictive tasks for abnormal event detection in videos—0
Spatio-Temporal Relation Learning for Video Anomaly Detection—0
Spatio-temporal Video Parsing for Abnormality Detection—0
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks—0
Spectral embedding of weighted graphs—0
Spectral-Spatial Extraction through Layered Tensor Decomposition for Hyperspectral Anomaly Detection—0
Speech motion anomaly detection via cross-modal translation of 4D motion fields from tagged MRI—0
SPICED: Syntactical Bug and Trojan Pattern Identification in A/MS Circuits using LLM-Enhanced Detection—0
SPINEX: Similarity-based Predictions with Explainable Neighbors Exploration for Anomaly and Outlier Detection—0
Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving—0
Squeezed Convolutional Variational AutoEncoder for Unsupervised Anomaly Detection in Edge Device Industrial Internet of Things—0
SIAD: Self-supervised Image Anomaly Detection System—0
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection—0
Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies—0
Stacked Residuals of Dynamic Layers for Time Series Anomaly Detection—0
STAN: Spatio-Temporal Adversarial Networks for Abnormal Event Detection—0
State Frequency Estimation for Anomaly Detection—0
Statistical Inference for Clustering-based Anomaly Detection—0
Statistical Inference Using Mean Shift Denoising—0
Statistical learning for change point and anomaly detection in graphs—0
Statistically Significant kNNAD by Selective Inference—0
Statistical Test for Anomaly Detections by Variational Auto-Encoders—0
Statistical Test on Diffusion Model-based Anomaly Detection by Selective Inference—0
Statistical testing on generative AI anomaly detection tools in Alzheimer's Disease diagnosis—0
Statistical validation of a deep learning algorithm for dental anomaly detection in intraoral radiographs using paired data—0
Statistics and Deep Learning-based Hybrid Model for Interpretable Anomaly Detection—0
Steam Turbine Anomaly Detection: An Unsupervised Learning Approach Using Enhanced Long Short-Term Memory Variational Autoencoder—0
STemGAN: spatio-temporal generative adversarial network for video anomaly detection—0
STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory Prediction—0
STNMamba: Mamba-based Spatial-Temporal Normality Learning for Video Anomaly Detection—0
Stochastic Earned Value Analysis using Monte Carlo Simulation and Statistical Learning Techniques—0
Stochastic Functional Analysis and Multilevel Vector Field Anomaly Detection—0
Stochastic tensor space feature theory with applications to robust machine learning—0
Stochastic Proximal AUC Maximization—0
"Stones from Other Hills can Polish Jade": Zero-shot Anomaly Image Synthesis via Cross-domain Anomaly Injection—0
Street Scene: A new dataset and evaluation protocol for video anomaly detection—0
Strengthening Anomaly Awareness—0
STRIC: Stacked Residuals of Interpretable Components for Time Series Anomaly Detection—0
Structural Teacher-Student Normality Learning for Multi-Class Anomaly Detection and Localization—0
Structure-based Anomaly Detection and Clustering—0
STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via—0
Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors—0
Study of the Impact of the Big Data Era on Accounting and Auditing—0
Sub-clusters of Normal Data for Anomaly Detection—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