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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 401–450 of 4856 papers

TitleStatusHype
Challenges in Visual Anomaly Detection for Mobile RobotsCode1
Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRICode1
ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The UnknownCode1
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth SimulationCode1
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
Combining GANs and AutoEncoders for Efficient Anomaly DetectionCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoTCode1
Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video EventsCode1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
AnoDFDNet: A Deep Feature Difference Network for Anomaly DetectionCode1
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly DetectionCode1
Collaborative Discrepancy Optimization for Reliable Image Anomaly LocalizationCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Eliciting Latent Knowledge from Quirky Language ModelsCode1
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
Enhancing the Analysis of Software Failures in Cloud Computing Systems with Deep LearningCode1
Complementary Pseudo Multimodal Feature for Point Cloud Anomaly DetectionCode1
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT SystemsCode1
Hard-normal Example-aware Template Mutual Matching for Industrial Anomaly DetectionCode1
Adversarial Anomaly Detection using Gaussian Priors and Nonlinear Anomaly ScoresCode1
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video DatasetCode1
A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-based Anomaly Detection TechniquesCode1
Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing FlowCode1
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier ExamplesCode1
Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly DetectionCode1
Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and AlgorithmsCode1
Dynamic Graph-Based Anomaly Detection in the Electrical GridCode1
Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical ImagesCode1
How To Backdoor Federated LearningCode1
Adversarially Learned Anomaly DetectionCode1
Continual Learning for Unsupervised Anomaly Detection in Continuous Auditing of Financial Accounting DataCode1
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive AlignmentCode1
Exathlon: A Benchmark for Explainable Anomaly Detection over Time SeriesCode1
AnomalyBERT: Self-Supervised Transformer for Time Series Anomaly Detection using Data Degradation SchemeCode1
AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-DecoderCode1
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly TypesCode1
ICSML: Industrial Control Systems ML Framework for native inference using IEC 61131-3 codeCode1
COOOL: Challenge Of Out-Of-Label A Novel Benchmark for Autonomous DrivingCode1
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR DataCode1
Dynamic Distinction Learning: Adaptive Pseudo Anomalies for Video Anomaly DetectionCode1
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly DetectionCode1
Active Anomaly Detection via EnsemblesCode1
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literatureCode1
Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly DetectionCode1
IM-IAD: Industrial Image Anomaly Detection Benchmark in ManufacturingCode1
Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly DetectionCode1
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile RobotsCode1
CutPaste: Self-Supervised Learning for Anomaly Detection and LocalizationCode1
Dual-path Frequency Discriminators for Few-shot Anomaly DetectionCode1
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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