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 501550 of 4856 papers

TitleStatusHype
Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame DetectionCode1
Anomaly Detection for Solder Joints Using β-VAECode1
A Shapelet-based Framework for Unsupervised Multivariate Time Series Representation LearningCode1
Anomaly Detection for Time Series Using VAE-LSTM Hybrid ModelCode1
COOOL: Challenge Of Out-Of-Label A Novel Benchmark for Autonomous DrivingCode1
Morphology-preserving Autoregressive 3D Generative Modelling of the BrainCode1
Coniferest: a complete active anomaly detection frameworkCode1
MRISegmentator-Abdomen: A Fully Automated Multi-Organ and Structure Segmentation Tool for T1-weighted Abdominal MRICode1
MSTREAM: Fast Anomaly Detection in Multi-Aspect StreamsCode1
Conformal Anomaly Detection on Spatio-Temporal Observations with Missing DataCode1
Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical ImagesCode1
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video DatasetCode1
Alleviating Structural Distribution Shift in Graph Anomaly DetectionCode1
Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing FlowCode1
Continual Learning for Unsupervised Anomaly Detection in Continuous Auditing of Financial Accounting DataCode1
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literatureCode1
Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New BaselineCode1
Collaborative Discrepancy Optimization for Reliable Image Anomaly LocalizationCode1
Combining GANs and AutoEncoders for Efficient Anomaly DetectionCode1
Clustered Hierarchical Anomaly and Outlier Detection AlgorithmsCode1
A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data StreamsCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Complementary Pseudo Multimodal Feature for Point Cloud Anomaly DetectionCode1
Class Label-aware Graph Anomaly DetectionCode1
Classification-Based Anomaly Detection for General DataCode1
CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly DetectionCode1
ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The UnknownCode1
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour modelsCode1
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth SimulationCode1
Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video EventsCode1
Component-aware anomaly detection framework for adjustable and logical industrial visual inspectionCode1
Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly DetectionCode1
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and ForecastingCode1
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data StreamCode1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
AlerTiger: Deep Learning for AI Model Health Monitoring at LinkedInCode1
Catching Both Gray and Black Swans: Open-set Supervised Anomaly DetectionCode1
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly DetectionCode1
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing FlowsCode1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly DetectionCode1
Can Multimodal LLMs Perform Time Series Anomaly Detection?Code1
CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event SequencesCode1
Camouflaged Object DetectionCode1
Calibrated One-class Classification for Unsupervised Time Series Anomaly DetectionCode1
Can LLMs Understand Time Series Anomalies?Code1
CHAD: Charlotte Anomaly DatasetCode1
Building an Automated and Self-Aware Anomaly Detection SystemCode1
BSDM: Background Suppression Diffusion Model for Hyperspectral Anomaly DetectionCode1
C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic ForecastingCode1
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR ImagesCode1
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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