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 351400 of 4856 papers

TitleStatusHype
CHAD: Charlotte Anomaly DatasetCode1
AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and LocalizationCode1
ADformer: A Multi-Granularity Transformer for EEG-Based Alzheimer's Disease AssessmentCode1
Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest RadiographsCode1
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-raysCode1
ADGym: Design Choices for Deep Anomaly DetectionCode1
Challenges in Visual Anomaly Detection for Mobile RobotsCode1
Deep Learning in Latent Space for Video Prediction and CompressionCode1
An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving VideosCode1
AnomalyBERT: Self-Supervised Transformer for Time Series Anomaly Detection using Data Degradation SchemeCode1
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing AnomaliesCode1
A Discrepancy Aware Framework for Robust Anomaly DetectionCode1
Delving into CLIP latent space for Video Anomaly RecognitionCode1
Demystifying Fraudulent Transactions and Illicit Nodes in the Bitcoin Network for Financial ForensicsCode1
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set RecognitionCode1
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural NetworksCode1
Detecting Anomalies within Time Series using Local Neural TransformationsCode1
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly DetectionCode1
Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention NetworksCode1
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly TypesCode1
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing FlowsCode1
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly DetectionCode1
Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRICode1
ADNet: Temporal Anomaly Detection in Surveillance VideosCode1
Diffusion Models for Medical Anomaly DetectionCode1
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly DetectionCode1
An End-to-End Computer Vision Methodology for Quantitative MetallographyCode1
A Comprehensive Survey of Regression Based Loss Functions for Time Series ForecastingCode1
Catching Both Gray and Black Swans: Open-set Supervised Anomaly DetectionCode1
Do Language Models Understand Time?Code1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and ForecastingCode1
CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event SequencesCode1
Dual-Distribution Discrepancy for Anomaly Detection in Chest X-RaysCode1
Dual-distribution discrepancy with self-supervised refinement for anomaly detection in medical imagesCode1
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time SeriesCode1
A Comprehensive Survey on Graph Anomaly Detection with Deep LearningCode1
Dynamic Distinction Learning: Adaptive Pseudo Anomalies for Video Anomaly DetectionCode1
Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and AlgorithmsCode1
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution FunctionsCode1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly DetectionCode1
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoTCode1
Eliciting Latent Knowledge from Quirky Language ModelsCode1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization ApproachCode1
Entropy Causal Graphs for Multivariate Time Series Anomaly DetectionCode1
ERX: A Fast Real-Time Anomaly Detection Algorithm for Hyperspectral Line ScanningCode1
Explainable Time Series Anomaly Detection using Masked Latent Generative ModelingCode1
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour 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