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 13261350 of 4856 papers

TitleStatusHype
SoftPatch: Unsupervised Anomaly Detection with Noisy DataCode2
Deep Learning for Trajectory Data Management and Mining: A Survey and BeyondCode3
Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly DetectionCode0
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly DetectionCode2
Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly DetectionCode1
Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data0
Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning0
Improving Interpretability of Scores in Anomaly Detection Based on Gaussian-Bernoulli Restricted Boltzmann Machine0
DMAD: Dual Memory Bank for Real-World Anomaly DetectionCode0
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly DetectionCode3
A Comparison of Deep Learning Architectures for Spacecraft Anomaly Detection0
Wildfire danger prediction optimization with transfer learningCode0
VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual NavigationCode1
Adapting Visual-Language Models for Generalizable Anomaly Detection in Medical ImagesCode3
Graph-Jigsaw Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection0
Learning Unified Reference Representation for Unsupervised Multi-class Anomaly DetectionCode1
Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?)0
Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly DetectionCode1
usfAD Based Effective Unknown Attack Detection Focused IDS Framework0
Tokensome: Towards a Genetic Vision-Language GPT for Explainable and Cognitive Karyotyping0
Customizing Visual-Language Foundation Models for Multi-modal Anomaly Detection and ReasoningCode1
Causality from Bottom to Top: A Survey0
Anomaly Detection Based on Isolation Mechanisms: A Survey0
DTOR: Decision Tree Outlier Regressor to explain anomaliesCode0
Generation is better than Modification: Combating High Class Homophily Variance in Graph 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