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 501–550 of 4856 papers

TitleStatusHype
FlexFringe: Modeling Software Behavior by Learning Probabilistic AutomataCode1
Anomaly Detection for Solder Joints Using β-VAECode1
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
Anomaly Detection for Time Series Using VAE-LSTM Hybrid ModelCode1
A SAM-guided Two-stream Lightweight Model for Anomaly DetectionCode1
DTAAD: Dual Tcn-Attention Networks for Anomaly Detection in Multivariate Time Series DataCode1
Alleviating Structural Distribution Shift in Graph Anomaly DetectionCode1
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly DetectionCode1
FLTracer: Accurate Poisoning Attack Provenance in Federated LearningCode1
Are we certain it's anomalous?Code1
Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly DetectionCode1
Few-shot Scene-adaptive Anomaly DetectionCode1
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data StreamsCode1
Few-Shot One-Class Classification via Meta-LearningCode1
FewSOME: One-Class Few Shot Anomaly Detection with Siamese NetworksCode1
Few-Shot Anomaly Detection via Category-Agnostic Registration LearningCode1
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative StudyCode1
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection AlgorithmsCode1
Few-Shot Anomaly Detection for Polyp Frames from ColonoscopyCode1
Few-shot Network Anomaly Detection via Cross-network Meta-learningCode1
F-FADE: Frequency Factorization for Anomaly Detection in Edge StreamsCode1
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly DetectionCode1
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly DetectionCode1
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data StreamCode1
Federated Foundation Models on Heterogeneous Time SeriesCode1
AlerTiger: Deep Learning for AI Model Health Monitoring at LinkedInCode1
Applying Surface Normal Information in Drivable Area and Road Anomaly Detection for Ground Mobile RobotsCode1
A Principled Approach to Enriching Security-related Data for Running Processes through Statistics and Natural Language ProcessingCode1
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data DetectionCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
FastLogAD: Log Anomaly Detection with Mask-Guided Pseudo Anomaly Generation and DiscriminationCode1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly LocalizationCode1
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing FlowsCode1
Fast Unsupervised Anomaly Detection in Traffic VideosCode1
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT NetworksCode1
Fast and Multi-aspect Mining of Complex Time-stamped Event StreamsCode1
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR DataCode1
FastAno: Fast Anomaly Detection via Spatio-temporal Patch TransformationCode1
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile RobotsCode1
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged ApproachCode1
Fast Distance-based Anomaly Detection in Images Using an Inception-like AutoencoderCode1
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
FAPM: Fast Adaptive Patch Memory for Real-time Industrial Anomaly DetectionCode1
AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly DetectionCode1
Fake It Till You Make It: Towards Accurate Near-Distribution Novelty DetectionCode1
Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution DetectionCode1
Anomaly localization by modeling perceptual featuresCode1
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language ModelsCode1
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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
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
7DDADDetection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9PBASDetection AUROC99.8—Unverified
10HETMMDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4DDADDetection AUROC98.9—Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
6INP-Former ViT-B (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