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 876900 of 4856 papers

TitleStatusHype
A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor DetectionCode1
Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and EvaluationCode1
Continuous Memory Representation for Anomaly DetectionCode1
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future ChallengesCode1
Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoTCode1
Learning image representations for anomaly detection: application to discovery of histological alterations in drug developmentCode1
Attention-based residual autoencoder for video anomaly detectionCode1
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networksCode1
HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly DetectionCode1
Asymmetric Student-Teacher Networks for Industrial Anomaly DetectionCode1
Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal AttentionCode1
Active Anomaly Detection via EnsemblesCode1
Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly DetectionCode1
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time seriesCode1
Toward Unsupervised 3D Point Cloud Anomaly Detection using Variational AutoencoderCode1
Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case StudyCode1
Learning Generalized Spoof Cues for Face Anti-spoofingCode1
How To Backdoor Federated LearningCode1
Anomaly Detection in Aerial Videos with TransformersCode1
An Attribute-based Method for Video Anomaly DetectionCode1
HSTforU: anomaly detection in aerial and ground-based videos with hierarchical spatio-temporal transformer for U-netCode1
Learning Graph Neural Networks for Multivariate Time Series Anomaly DetectionCode1
Learning Latent Space Energy-Based Prior ModelCode1
Hybrid Open-set Segmentation with Synthetic Negative DataCode1
Learning to Adapt to Unseen Abnormal Activities under Weak SupervisionCode1
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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