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 526550 of 4856 papers

TitleStatusHype
Anomaly Detection using Score-based Perturbation ResilienceCode1
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT NetworksCode1
SiteFerret: beyond simple pocket identification in proteinsCode1
CHAD: Charlotte Anomaly DatasetCode1
FedTADBench: Federated Time-Series Anomaly Detection BenchmarkCode1
Lorentz group equivariant autoencodersCode1
CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly DetectionCode1
On Root Cause Localization and Anomaly Mitigation through Causal InferenceCode1
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive AlignmentCode1
An Attribute-based Method for Video Anomaly DetectionCode1
MGFN: Magnitude-Contrastive Glance-and-Focus Network for Weakly-Supervised Video Anomaly DetectionCode1
Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic SegmentationCode1
MAEDAY: MAE for few and zero shot AnomalY-DetectionCode1
RbA: Segmenting Unknown Regions Rejected by AllCode1
PNI : Industrial Anomaly Detection using Position and Neighborhood InformationCode1
U-Flow: A U-shaped Normalizing Flow for Anomaly Detection with Unsupervised ThresholdCode1
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly DetectionCode1
Normalizing Flows for Human Pose Anomaly DetectionCode1
Are we certain it's anomalous?Code1
Anomaly Detection in Multiplex Dynamic Networks: from Blockchain Security to Brain Disease PredictionCode1
FAPM: Fast Adaptive Patch Memory for Real-time Industrial Anomaly DetectionCode1
LGN-Net: Local-Global Normality Network for Video Anomaly DetectionCode1
Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution DetectionCode1
Deep Learning for Time Series Anomaly Detection: A SurveyCode1
A Comprehensive Survey of Regression Based Loss Functions for Time Series ForecastingCode1
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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
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (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