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 576600 of 4856 papers

TitleStatusHype
An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving VideosCode1
Deep Feature Selection for Anomaly Detection Based on Pretrained Network and Gaussian Discriminative AnalysisCode1
W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series ForecastingCode1
Morphology-preserving Autoregressive 3D Generative Modelling of the BrainCode1
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human DiseaseCode1
nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation MethodsCode1
Q-Net: Query-Informed Few-Shot Medical Image SegmentationCode1
Unsupervised Anomaly Localization with Structural Feature-AutoencodersCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
SensorSCAN: Self-Supervised Learning and Deep Clustering for Fault Diagnosis in Chemical ProcessesCode1
CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event SequencesCode1
Unsupervised Face Morphing Attack Detection via Self-paced Anomaly DetectionCode1
Detecting Multivariate Time Series Anomalies with Zero Known LabelCode1
DSR -- A dual subspace re-projection network for surface anomaly detectionCode1
Calibrated One-class Classification for Unsupervised Time Series Anomaly DetectionCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly DetectionCode1
Video Anomaly Detection by Solving Decoupled Spatio-Temporal Jigsaw PuzzlesCode1
Informative knowledge distillation for image anomaly segmentationCode1
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
Deep Learning for Anomaly Detection in Log Data: A SurveyCode1
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set RecognitionCode1
Leveraging Trajectory Prediction for Pedestrian Video Anomaly DetectionCode1
Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly DetectionCode1
Deep Contrastive One-Class Time Series Anomaly DetectionCode1
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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