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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 1851–1875 of 4856 papers

TitleStatusHype
Model Evaluation and Anomaly Detection in Temporal Complex Networks using Deep Learning Methods—0
Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System TelemetryCode0
Weakly-supervised anomaly detection for multimodal data distributions—0
Anomaly Detection Utilizing a Riemann Metric for Robust Myoelectric Pattern Recognition—0
Enhanced Anomaly Detection in Automotive Systems Using SAAD: Statistical Aggregated Anomaly Detection—0
Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection—0
UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving—0
Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving—0
fSEAD: a Composable FPGA-based Streaming Ensemble Anomaly Detection LibraryCode0
RAPID: Robust APT Detection and Investigation Using Context-Aware Deep Learning—0
Attention Fusion Reverse Distillation for Multi-Lighting Image Anomaly Detection—0
VisionAD, a software package of performant anomaly detection algorithms, and Proportion Localised, an interpretable metricCode0
A Recover-then-Discriminate Framework for Robust Anomaly Detection—0
GANetic Loss for Generative Adversarial Networks with a Focus on Medical ApplicationsCode0
Higher-order Structure Based Anomaly Detection on Attributed Networks—0
Enhancing Large-Scale AI Training Efficiency: The C4 Solution for Real-Time Anomaly Detection and Communication Optimization—0
Continuous Test-time Domain Adaptation for Efficient Fault Detection under Evolving Operating Conditions—0
Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models—0
Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection—0
Advancing Anomaly Detection: Non-Semantic Financial Data Encoding with LLMs—0
A Comprehensive Library for Benchmarking Multi-class Visual Anomaly Detection—0
DA-Flow: Dual Attention Normalizing Flow for Skeleton-based Video Anomaly Detection—0
Multivariate Physics-Informed Convolutional Autoencoder for Anomaly Detection in Power Distribution Systems with High Penetration of DERs—0
M3DM-NR: RGB-3D Noisy-Resistant Industrial Anomaly Detection via Multimodal Denoising—0
Pancreatic Tumor Segmentation as Anomaly Detection in CT Images Using Denoising Diffusion Models—0
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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