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 1051–1100 of 4856 papers

TitleStatusHype
Support Vector Based Anomaly Detection in Federated Learning—0
SOWA: Adapting Hierarchical Frozen Window Self-Attention to Visual-Language Models for Better Anomaly DetectionCode1
Early-Stage Anomaly Detection: A Study of Model Performance on Complete vs. Partial FlowsCode0
Unified Anomaly Detection methods on Edge Device using Knowledge Distillation and Quantization—0
Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization—0
Domain-independent detection of known anomaliesCode0
LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log AnalysisCode1
Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining TasksCode0
Enhancing Multi-Class Anomaly Detection via Diffusion Refinement with Dual Conditioning—0
Counterfactual Data Augmentation with Denoising Diffusion for Graph Anomaly DetectionCode0
HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly DetectionCode1
ToCoAD: Two-Stage Contrastive Learning for Industrial Anomaly Detection—0
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based ModelsCode1
The OPS-SAT benchmark for detecting anomalies in satellite telemetryCode1
Infrared Computer Vision for Utility-Scale Photovoltaic Array Inspection—0
Real-Time Energy Measurement for Non-Intrusive Well-Being Monitoring of Elderly People -- a Case Study—0
FANFOLD: Graph Normalizing Flows-driven Asymmetric Network for Unsupervised Graph-Level Anomaly DetectionCode0
ModeConv: A Novel Convolution for Distinguishing Anomalous and Normal Structural BehaviorCode0
Localizing Anomalies via Multiscale Score Matching AnalysisCode0
xSemAD: Explainable Semantic Anomaly Detection in Event Logs Using Sequence-to-Sequence ModelsCode0
Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly DetectionCode1
Odd-One-Out: Anomaly Detection by Comparing with NeighborsCode2
CHASE: A Causal Heterogeneous Graph based Framework for Root Cause Analysis in Multimodal Microservice Systems—0
Hack Me If You Can: Aggregating AutoEncoders for Countering Persistent Access Threats Within Highly Imbalanced DataCode0
CLIP3D-AD: Extending CLIP for 3D Few-Shot Anomaly Detection with Multi-View Images Generation—0
Looking 3D: Anomaly Detection with 2D-3D AlignmentCode1
MissionGNN: Hierarchical Multimodal GNN-based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation—0
Human-Free Automated Prompting for Vision-Language Anomaly Detection: Prompt Optimization with Meta-guiding Prompt Scheme—0
View-Invariant Pixelwise Anomaly Detection in Multi-object Scenes with Adaptive View Synthesis—0
Anomaly detection with a variational autoencoder for Arabic mispronunciation detection—0
European Space Agency Benchmark for Anomaly Detection in Satellite TelemetryCode2
SincVAE: a New Approach to Improve Anomaly Detection on EEG Data Using SincNet and Variational Autoencoder—0
Robust Zero Trust Architecture: Joint Blockchain based Federated learning and Anomaly Detection based Framework—0
Integrating Generative AI with Network Digital Twins for Enhanced Network Operations—0
Anomaly Detection of Tabular Data Using LLMs—0
Detecting Abnormal Operations in Concentrated Solar Power Plants from Irregular Sequences of Thermal ImagesCode0
DABL: Detecting Semantic Anomalies in Business Processes Using Large Language ModelsCode0
Root Cause Analysis of Anomalies in 5G RAN Using Graph Neural Network and Transformer—0
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A BenchmarkCode2
AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics—0
FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalous Event DetectionCode0
aeon: a Python toolkit for learning from time seriesCode5
ATAC-Net: Zoomed view works better for Anomaly Detection—0
Image anomaly detection and prediction scheme based on SSA optimized ResNet50-BiGRU model—0
Tracking Real-time Anomalies in Cyber-Physical Systems Through Dynamic Behavioral Analysis—0
Self-Supervised Time-Series Anomaly Detection Using Learnable Data Augmentation—0
Online-Adaptive Anomaly Detection for Defect Identification in Aircraft Assembly—0
Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLMCode2
Prior Normality Prompt Transformer for Multi-class Industrial Image Anomaly Detection—0
VideoVista: A Versatile Benchmark for Video Understanding and ReasoningCode1
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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