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 51–75 of 4856 papers

TitleStatusHype
IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical DomainCode0
Data Driven Diagnosis for Large Cyber-Physical-Systems with Minimal Prior Information—0
Conditional diffusion models for guided anomaly detection in brain images using fluid-driven anomaly randomization—0
Wavelet Scattering Transform and Fourier Representation for Offline Detection of Malicious Clients in Federated Learning—0
An Explainable Deep Learning Framework for Brain Stroke and Tumor Progression via MRI Interpretation—0
PatchGuard: Adversarially Robust Anomaly Detection and Localization through Vision Transformers and Pseudo AnomaliesCode1
Integrating Asynchronous AdaBoost into Federated Learning: Five Real World Applications—0
HomographyAD: Deep Anomaly Detection Using Self Homography Learning—0
MAMBO: High-Resolution Generative Approach for Mammography Images—0
Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization—0
Cross-Entropy Games for Language Models: From Implicit Knowledge to General Capability Measures—0
MLOps with Microservices: A Case Study on the Maritime Domain—0
Noise-Driven AI Sensors: Secure Healthcare Monitoring with PUFs—0
Track Any Anomalous Object: A Granular Video Anomaly Detection Pipeline—0
Federated Isolation Forest for Efficient Anomaly Detection on Edge IoT Systems—0
INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual LearningCode3
An AI-Based Public Health Data Monitoring System—0
System Calls for Malware Detection and Classification: Methodologies and Applications—0
Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series—0
Generator Based Inference (GBI)Code0
Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHCCode0
KairosAD: A SAM-Based Model for Industrial Anomaly Detection on Embedded DevicesCode0
Bridging 3D Anomaly Localization and Repair via High-Quality Continuous Geometric RepresentationCode0
Anomaly Detection and Improvement of Clusters using Enhanced K-Means Algorithm—0
SentinelAgent: Graph-based Anomaly Detection in Multi-Agent Systems—0
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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