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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 651–700 of 4856 papers

TitleStatusHype
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly DetectionCode1
First-shot anomaly sound detection for machine condition monitoring: A domain generalization baselineCode1
CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly DetectionCode1
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth SimulationCode1
ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The UnknownCode1
Classification-Based Anomaly Detection for General DataCode1
FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series ClassificationCode1
FUN-AD: Fully Unsupervised Learning for Anomaly Detection with Noisy Training DataCode1
Functional Isolation ForestCode1
Future Frame Prediction for Anomaly Detection – A New BaselineCode1
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly DetectionCode1
Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video EventsCode1
Challenges in Visual Anomaly Detection for Mobile RobotsCode1
CHAD: Charlotte Anomaly DatasetCode1
A Multi-Scale Decomposition MLP-Mixer for Time Series AnalysisCode1
Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRICode1
Generative Adversarial Network with Soft-Dynamic Time Warping and Parallel Reconstruction for Energy Time Series Anomaly DetectionCode1
Generative and Contrastive Self-Supervised Learning for Graph Anomaly DetectionCode1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and ForecastingCode1
GlocalCLIP: Object-agnostic Global-Local Prompt Learning for Zero-shot Anomaly DetectionCode1
Graph Anomaly Detection with Unsupervised GNNsCode1
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing FlowsCode1
Graph Neural Network-Based Anomaly Detection in Multivariate Time SeriesCode1
Graph Neural Network-Based Anomaly Detection for River Network SystemsCode1
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour modelsCode1
Clustered Hierarchical Anomaly and Outlier Detection AlgorithmsCode1
Anomaly Detection with Score Distribution DiscriminationCode1
Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame DetectionCode1
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human DiseaseCode1
Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal AttentionCode1
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition SoundsCode1
Can Multimodal LLMs Perform Time Series Anomaly Detection?Code1
How To Backdoor Federated LearningCode1
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time seriesCode1
Can LLMs Understand Time Series Anomalies?Code1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly DetectionCode1
Calibrated One-class Classification for Unsupervised Time Series Anomaly DetectionCode1
ICSML: Industrial Control Systems ML Framework for native inference using IEC 61131-3 codeCode1
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly DetectionCode1
CwA-T: A Channelwise AutoEncoder with Transformer for EEG Abnormality DetectionCode1
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly DetectionCode1
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly DetectionCode1
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language ModelsCode1
Improving Generalizability of Graph Anomaly Detection Models via Data AugmentationCode1
Anomaly localization by modeling perceptual featuresCode1
Improving Position Encoding of Transformers for Multivariate Time Series ClassificationCode1
Camouflaged Object DetectionCode1
CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event SequencesCode1
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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
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
7DDADDetection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9PBASDetection AUROC99.8—Unverified
10HETMMDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4DDADDetection AUROC98.9—Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
6INP-Former ViT-B (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