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 17511775 of 4856 papers

TitleStatusHype
SR-CIS: Self-Reflective Incremental System with Decoupled Memory and Reasoning0
AnomalySD: Few-Shot Multi-Class Anomaly Detection with Stable Diffusion Model0
Individualized multi-horizon MRI trajectory prediction for Alzheimer's DiseaseCode0
Online Detection of Anomalies in Temporal Knowledge Graphs with InterpretabilityCode0
Efficient Quantum One-Class Support Vector Machines for Anomaly Detection Using Randomized Measurements and Variable Subsampling0
Time Series Anomaly Detection with CNN for Environmental Sensors in Healthcare-IoT0
Normality Addition via Normality Detection in Industrial Image Anomaly Detection Models0
Foundations for Unfairness in Anomaly Detection -- Case Studies in Facial Imaging Data0
Anomalous State Sequence Modeling to Enhance Safety in Reinforcement Learning0
Can I trust my anomaly detection system? A case study based on explainable AICode0
Textile Anomaly Detection: Evaluation of the State-of-the-Art for Automated Quality Inspection of Carpet0
Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-time Lightweight Time Series Anomaly Detection0
Separating Novel Features for Logical Anomaly Detection: A Straightforward yet Effective Approach0
Looking at Model Debiasing through the Lens of Anomaly DetectionCode0
When Text and Images Don't Mix: Bias-Correcting Language-Image Similarity Scores for Anomaly Detection0
Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context LearningCode0
Global Confidence Degree Based Graph Neural Network for Financial Fraud Detection0
Hyperbolic embedding of brain networks detects regions disrupted by neurodegeneration in Alzheimer's disease0
Towards Open-World Object-based Anomaly Detection via Self-Supervised Outlier SynthesisCode0
Bidirectional skip-frame prediction for video anomaly detection with intra-domain disparity-driven attention0
Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound0
Synthetic Time Series for Anomaly Detection in Cloud Microservices0
Decentralized Federated Anomaly Detection in Smart Grids: A P2P Gossip Approach0
TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision0
Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection0
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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