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 401–450 of 4856 papers

TitleStatusHype
Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution DetectionCode1
Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale LearningCode1
FastAno: Fast Anomaly Detection via Spatio-temporal Patch TransformationCode1
Fast Distance-based Anomaly Detection in Images Using an Inception-like AutoencoderCode1
An Incremental Unified Framework for Small Defect InspectionCode1
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing FlowsCode1
Federated Foundation Models on Heterogeneous Time SeriesCode1
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data DetectionCode1
Federated PCA on Grassmann Manifold for IoT Anomaly DetectionCode1
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly DetectionCode1
AnoDFDNet: A Deep Feature Difference Network for Anomaly DetectionCode1
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly DetectionCode1
Class Label-aware Graph Anomaly DetectionCode1
Few-shot Network Anomaly Detection via Cross-network Meta-learningCode1
Clustered Hierarchical Anomaly and Outlier Detection AlgorithmsCode1
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour modelsCode1
Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRICode1
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly DetectionCode1
ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The UnknownCode1
FlexFringe: Modeling Software Behavior by Learning Probabilistic AutomataCode1
CHAD: Charlotte Anomaly DatasetCode1
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly DetectionCode1
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing FlowsCode1
FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series ClassificationCode1
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier ExamplesCode1
Fully Convolutional Cross-Scale-Flows for Image-based Defect DetectionCode1
Future Frame Prediction for Anomaly Detection -- A New BaselineCode1
Future Frame Prediction for Anomaly Detection – A New BaselineCode1
GAD-NR: Graph Anomaly Detection via Neighborhood ReconstructionCode1
GAN Ensemble for Anomaly DetectionCode1
Challenges in Visual Anomaly Detection for Mobile RobotsCode1
Generalized Out-of-Distribution Detection: A SurveyCode1
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth SimulationCode1
Exathlon: A Benchmark for Explainable Anomaly Detection over Time SeriesCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Catching Both Gray and Black Swans: Open-set Supervised Anomaly DetectionCode1
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly TypesCode1
Generator Versus Segmentor: Pseudo-healthy SynthesisCode1
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly DetectionCode1
GlocalCLIP: Object-agnostic Global-Local Prompt Learning for Zero-shot Anomaly DetectionCode1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly DetectionCode1
Graph Anomaly Detection with Unsupervised GNNsCode1
Can Multimodal LLMs Perform Time Series Anomaly Detection?Code1
Graph-level Anomaly Detection via Hierarchical Memory NetworksCode1
CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event SequencesCode1
Graph Neural Networks based Log Anomaly Detection and ExplanationCode1
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and ForecastingCode1
Calibrated One-class Classification for Unsupervised Time Series Anomaly DetectionCode1
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human DiseaseCode1
Camouflaged Object DetectionCode1
Show:102550
← PrevPage 9 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