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

Showing 401450 of 4856 papers

TitleStatusHype
OutRank: Speeding up AutoML-based Model Search for Large Sparse Data sets with Cardinality-aware Feature RankingCode1
Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly LocalizationCode1
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRICode1
MSFlow: Multi-Scale Flow-based Framework for Unsupervised Anomaly DetectionCode1
HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural NetworksCode1
REB: Reducing Biases in Representation for Industrial Anomaly DetectionCode1
Class Label-aware Graph Anomaly DetectionCode1
TeD-SPAD: Temporal Distinctiveness for Self-supervised Privacy-preservation for video Anomaly DetectionCode1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly DetectionCode1
On the Effectiveness of Log Representation for Log-based Anomaly DetectionCode1
Interpretable Online Log Analysis Using Large Language Models with Prompt StrategiesCode1
ImbSAM: A Closer Look at Sharpness-Aware Minimization in Class-Imbalanced RecognitionCode1
Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch RetrievalCode1
Out-of-Distribution Detection for Monocular Depth EstimationCode1
Multi-Class Deep SVDD: Anomaly Detection Approach in Astronomy with Distinct Inlier CategoriesCode1
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly DetectionCode1
UGainS: Uncertainty Guided Anomaly Instance SegmentationCode1
Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly DetectionCode1
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain ImagesCode1
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization ApproachCode1
RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous SupervisionCode1
Unmasking Anomalies in Road-Scene SegmentationCode1
Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and ModelCode1
UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly DetectionCode1
Optimizing PatchCore for Few/many-shot Anomaly DetectionCode1
BSDM: Background Suppression Diffusion Model for Hyperspectral Anomaly DetectionCode1
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly DetectionCode1
Masked Autoencoders for Unsupervised Anomaly Detection in Medical ImagesCode1
Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly DetectionCode1
PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and SegmentationCode1
ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The UnknownCode1
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT SystemsCode1
Unsupervised Video Anomaly Detection with Diffusion Models Conditioned on Compact Motion RepresentationsCode1
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly DetectionCode1
Graph-level Anomaly Detection via Hierarchical Memory NetworksCode1
Graph Neural Networks based Log Anomaly Detection and ExplanationCode1
Precursor-of-Anomaly Detection for Irregular Time SeriesCode1
Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly DetectionCode1
Anomaly Detection with Score Distribution DiscriminationCode1
Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly DetectorsCode1
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly DetectionCode1
BMAD: Benchmarks for Medical Anomaly DetectionCode1
Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public ProcurementCode1
Improving Generalizability of Graph Anomaly Detection Models via Data AugmentationCode1
ReContrast: Domain-Specific Anomaly Detection via Contrastive ReconstructionCode1
UADB: Unsupervised Anomaly Detection BoosterCode1
AlerTiger: Deep Learning for AI Model Health Monitoring at LinkedInCode1
GAD-NR: Graph Anomaly Detection via Neighborhood ReconstructionCode1
Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion ModelCode1
Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
7DDADDetection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9PBASDetection AUROC99.8Unverified
10HETMMDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4DDADDetection AUROC98.9Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
6INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified