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 36013625 of 4856 papers

TitleStatusHype
TrustMAE: A Noise-Resilient Defect Classification Framework using Memory-Augmented Auto-Encoders with Trust Regions0
A Comprehensive Guide to CAN IDS Data & Introduction of the ROAD Dataset0
Towards Fair Deep Anomaly Detection0
Detecting Anomalous Invoice Line Items in the Legal Case Lifecycle0
Recomposition vs. Prediction: A Novel Anomaly Detection for Discrete Events Based On AutoencoderCode0
Time-Window Group-Correlation Support vs. Individual Features: A Detection of Abnormal UsersCode0
Neural Networks, Artificial Intelligence and the Computational Brain0
Camouflaged Object Detection and Tracking: A Survey0
Graph Convolutional Networks for traffic anomalyCode1
Am I Rare? An Intelligent Summarization Approach for Identifying Hidden Anomalies0
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge GraphsCode1
Identification of Unexpected Decisions in Partially Observable Monte-Carlo Planning: a Rule-Based ApproachCode0
General Domain Adaptation Through Proportional Progressive Pseudo LabelingCode0
Dual-encoder Bidirectional Generative Adversarial Networks for Anomaly Detection0
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation0
Improving unsupervised anomaly localization by applying multi-scale memories to autoencoders0
Unsupervised Anomaly Detectors to Detect Intrusions in the Current Threat Landscape0
Computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation0
Image-Based Jet Analysis0
Anomaly Detection and Localization based on Double Kernelized Scoring and Matrix Kernels0
Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative FrameworkCode0
A Systematic Mapping Study in AIOps0
Multi-Modal Anomaly Detection for Unstructured and Uncertain EnvironmentsCode1
GAN Ensemble for Anomaly DetectionCode1
DFR: Deep Feature Reconstruction for Unsupervised Anomaly SegmentationCode1
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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