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 1651–1700 of 4856 papers

TitleStatusHype
A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor DetectionCode1
Temporal Shift -- Multi-Objective Loss Function for Improved Anomaly Fall Detection—0
Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case StudyCode1
GPT-4V-AD: Exploring Grounding Potential of VQA-oriented GPT-4V for Zero-shot Anomaly DetectionCode1
Sketching Multidimensional Time Series for Fast Discord Mining—0
Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the LeadCode1
AIOps-Driven Enhancement of Log Anomaly Detection in Unsupervised Scenarios—0
MTS-DVGAN: Anomaly Detection in Cyber-Physical Systems using a Dual Variational Generative Adversarial Network—0
Holistic Representation Learning for Multitask Trajectory Anomaly DetectionCode1
InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV ImagesCode1
Respiratory Anomaly Detection using Reflected Infrared Light-wave Signals—0
Time Series Anomaly Detection using Diffusion-based ModelsCode1
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth SimulationCode1
Few-shot time-series anomaly detection with unsupervised domain adaptation—0
Model-driven Engineering for Machine Learning Components: A Systematic Literature Review—0
Architecture of Data Anomaly Detection-Enhanced Decentralized Expert System for Early-Stage Alzheimer's Disease Prediction—0
CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection—0
Log-based Anomaly Detection of Enterprise Software: An Empirical Study—0
A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks—0
Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection—0
MENTOR: Human Perception-Guided Pretraining for Increased Generalization—0
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental LearningCode0
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly DetectionCode2
Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly DetectionCode1
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach—0
Debunking Free Fusion Myth: Online Multi-view Anomaly Detection with Disentangled Product-of-Experts Modeling—0
MEDAVET: Traffic Vehicle Anomaly Detection Mechanism based on spatial and temporal structures in vehicle traffic—0
Adversarial Anomaly Detection using Gaussian Priors and Nonlinear Anomaly ScoresCode1
Understanding Parameter Saliency via Extreme Value Theory—0
OrionBench: Benchmarking Time Series Generative Models in the Service of the End-User—0
MIM-GAN-based Anomaly Detection for Multivariate Time Series DataCode0
Detecting subtle cyberattacks on adaptive cruise control vehicles: A machine learning approach—0
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly DetectionCode1
Towards Self-Interpretable Graph-Level Anomaly DetectionCode1
GADY: Unsupervised Anomaly Detection on Dynamic Graphs—0
On Pixel-level Performance Assessment in Anomaly Detection—0
Localizing Anomalies in Critical Infrastructure using Model-Based Drift ExplanationsCode0
One or Two Things We know about Concept Drift -- A Survey on Monitoring Evolving Environments—0
ADoPT: LiDAR Spoofing Attack Detection Based on Point-Level Temporal Consistency—0
CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference—0
Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly DetectionCode1
Concept-based Anomaly Detection in Retail Stores for Automatic Correction using Mobile Robots—0
An Event based Prediction Suffix Tree—0
Positive-Unlabeled Node Classification with Structure-aware Graph Learning—0
FLTracer: Accurate Poisoning Attack Provenance in Federated LearningCode1
Identification of Abnormality in Maize Plants From UAV Images Using Deep Learning Approaches—0
Anomaly Detection of Command Shell Sessions based on DistilBERT: Unsupervised and Supervised Approaches—0
SigML++: Supervised Log Anomaly with Probabilistic Polynomial Approximation—0
A New Time Series Similarity Measure and Its Smart Grid Applications—0
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly DetectionCode1
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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