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 1351–1400 of 4856 papers

TitleStatusHype
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model—0
Sequential PatchCore: Anomaly Detection for Surface Inspection using Synthetic Impurities—0
ComplexVAD: Detecting Interaction Anomalies in Video—0
Transformer-based Multivariate Time Series Anomaly Localization—0
STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via—0
Detecting Contextual Anomalies by Discovering Consistent Spatial Regions—0
Unsupervised Feature Construction for Anomaly Detection in Time Series -- An Evaluation—0
Multiple-Input Variational Auto-Encoder for Anomaly Detection in Heterogeneous Data—0
ADKGD: Anomaly Detection in Knowledge Graphs with Dual-Channel TrainingCode0
Driver Age and Its Effect on Key Driving Metrics: Insights from Dynamic Vehicle Data—0
Generative AI Enabled Robust Sensor Placement in Cyber-Physical Power Systems: A Graph Diffusion Approach—0
Active Rule Mining for Multivariate Anomaly Detection in Radio Access Networks—0
Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural NetworksCode0
Explaining Deep Learning-based Anomaly Detection in Energy Consumption Data by Focusing on Contextually Relevant Data—0
Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection—0
Learning Compact and Robust Representations for Anomaly Detection—0
EVA-S2PLoR: A Secure Element-wise Multiplication Meets Logistic Regression on Heterogeneous Database—0
Back Home: A Machine Learning Approach to Seashell Classification and Ecosystem Restoration—0
Planing It by Ear: Convolutional Neural Networks for Acoustic Anomaly Detection in Industrial Wood PlanersCode0
Quantum Hybrid Support Vector Machines for Stress Detection in Older Adults—0
Leveraging Registers in Vision Transformers for Robust Adaptation—0
KAnoCLIP: Zero-Shot Anomaly Detection through Knowledge-Driven Prompt Learning and Enhanced Cross-Modal Integration—0
GraphDART: Graph Distillation for Efficient Advanced Persistent Threat Detection—0
On the Adversarial Robustness of Benjamini Hochberg—0
Unsupervised Tomato Split Anomaly Detection using Hyperspectral Imaging and Variational Autoencoders—0
Self-Supervised Learning for Detecting AI-Generated Faces as AnomaliesCode0
Multivariate Time Series Anomaly Detection using DiffGAN ModelCode0
Counterfactual Explanation for Auto-Encoder Based Time-Series Anomaly Detection—0
LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction—0
Training Medical Large Vision-Language Models with Abnormal-Aware Feedback—0
An Efficient Outlier Detection Algorithm for Data Streaming—0
InDeed: Interpretable image deep decomposition with guaranteed generalizability—0
Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection—0
Track Any Anomalous Object:A Granular Video Anomaly Detection Pipeline—0
DFM: Differentiable Feature Matching for Anomaly Detection—0
A Unified Latent Schrodinger Bridge Diffusion Model for Unsupervised Anomaly Detection and Localization—0
Unseen Visual Anomaly Generation—0
PIAD: Pose and Illumination agnostic Anomaly Detection—0
Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation—0
Just Dance with pi! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection—0
Noise-Resistant Video Anomaly Detection via RGB Error-Guided Multiscale Predictive Coding and Dynamic Memory—0
OralXrays-9: Towards Hospital-Scale Panoramic X-ray Anomaly Detection via Personalized Multi-Object Query-Aware Mining—0
TAGA: Self-supervised Learning for Template-free Animatable Gaussian Articulated Model—0
Beyond Single-Modal Boundary: Cross-Modal Anomaly Detection through Visual Prototype and HarmonizationCode0
CNC: Cross-modal Normality Constraint for Unsupervised Multi-class Anomaly Detection—0
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework—0
Machine Learning-Based Security Policy Analysis—0
Exploring the Magnitude-Shape Plot Framework for Anomaly Detection in Crowded Video Scenes—0
A Survey on Time-Series Distance Measures—0
Cross-Modal Fusion and Attention Mechanism for Weakly Supervised Video Anomaly Detection—0
Show:102550
← PrevPage 28 of 98Next →
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