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 576–600 of 4856 papers

TitleStatusHype
Robust PCA Based on Adaptive Weighted Least Squares and Low-Rank Matrix Factorization—0
CwA-T: A Channelwise AutoEncoder with Transformer for EEG Abnormality DetectionCode1
Global Spatio-Temporal Fusion-based Traffic Prediction Algorithm with Anomaly Aware—0
Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary Learning Framework for Abnormality Detection and Report GenerationCode0
Quantum Machine Learning in Log-based Anomaly Detection: Challenges and Opportunities—0
Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly DetectionCode1
Do Language Models Understand Time?Code1
BadSAD: Clean-Label Backdoor Attacks against Deep Semi-Supervised Anomaly Detection—0
PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection—0
Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial LearningCode1
Synthetic Data Generation for Anomaly Detection on Table GrapesCode0
AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAP—0
Robust Spectral Anomaly Detection in EELS Spectral Images via Three Dimensional Convolutional Variational AutoencodersCode0
Are Large Language Models Useful for Time Series Data Analysis?—0
F-RBA: A Federated Learning-based Framework for Risk-based Authentication—0
Unsupervised Anomaly Detection for Tabular Data Using Noise Evaluation—0
AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and LocalizationCode1
Learning Set Functions with Implicit Differentiation—0
AD-LLM: Benchmarking Large Language Models for Anomaly DetectionCode1
Know Unreported Roadway Incidents in Real-time: A Deep Learning Framework for Early Traffic Anomaly Detection—0
Audio-based Anomaly Detection in Industrial Machines Using Deep One-Class Support Vector Data Description—0
FDM-Bench: A Comprehensive Benchmark for Evaluating Large Language Models in Additive Manufacturing TasksCode0
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly DetectionCode1
Video Anomaly Detection with Motion and Appearance Guided Patch Diffusion ModelCode1
Federated Foundation Models on Heterogeneous Time SeriesCode1
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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