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

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Showing 26–50 of 4856 papers

TitleStatusHype
Experimental Assessment of Neural 3D Reconstruction for Small UAV-based Applications—0
Sequential keypoint density estimator: an overlooked baseline of skeleton-based video anomaly detectionCode1
Trustworthy Prediction with Gaussian Process Knowledge ScoresCode0
Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017—0
TAB: Unified Benchmarking of Time Series Anomaly Detection MethodsCode2
Quantum-Hybrid Support Vector Machines for Anomaly Detection in Industrial Control Systems—0
Searching for a Hidden Markov Anomaly over Multiple Processes—0
Signatures to help interpretability of anomalies—0
Noise Fusion-based Distillation Learning for Anomaly Detection in Complex Industrial Environments—0
Evaluation Pipeline for systematically searching for Anomaly Detection Systems—0
Determinação Automática de Limiar de Detecção de Ataques em Redes de Computadores Utilizando Autoencoders—0
Explain First, Trust Later: LLM-Augmented Explanations for Graph-Based Crypto Anomaly DetectionCode0
Latent Anomaly Detection: Masked VQ-GAN for Unsupervised Segmentation in Medical CBCT—0
Condition Monitoring with Machine Learning: A Data-Driven Framework for Quantifying Wind Turbine Energy Loss—0
Polyra Swarms: A Shape-Based Approach to Machine Learning—0
Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies—0
Probing Deep into Temporal Profile Makes the Infrared Small Target Detector Much BetterCode1
SmartHome-Bench: A Comprehensive Benchmark for Video Anomaly Detection in Smart Homes Using Multi-Modal Large Language ModelsCode1
Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles—0
Temporal cross-validation impacts multivariate time series subsequence anomaly detection evaluation—0
Self-supervised Learning of Echocardiographic Video Representations via Online Cluster DistillationCode1
Prioritizing Alignment Paradigms over Task-Specific Model Customization in Time-Series LLMsCode0
Diffusion-Based Electrocardiography Noise Quantification via Anomaly DetectionCode1
Deep Symmetric Autoencoders from the Eckart-Young-Schmidt PerspectiveCode0
Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive MappingCode1
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All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified