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 251–300 of 4856 papers

TitleStatusHype
A Survey of World Models for Autonomous DrivingCode1
BMAD: Benchmarks for Medical Anomaly DetectionCode1
DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing AnomaliesCode1
Demystifying Fraudulent Transactions and Illicit Nodes in the Bitcoin Network for Financial ForensicsCode1
DFR: Deep Feature Reconstruction for Unsupervised Anomaly SegmentationCode1
Do Language Models Understand Time?Code1
AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-DecoderCode1
A Comprehensive Survey of Regression Based Loss Functions for Time Series ForecastingCode1
Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly LocalizationCode1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
ADNet: Temporal Anomaly Detection in Surveillance VideosCode1
Deep Learning in Latent Space for Video Prediction and CompressionCode1
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR DataCode1
Deep Learning for Anomaly Detection in Log Data: A SurveyCode1
Deep Learning for Gamma-Ray Bursts: A data driven event framework for X/Gamma-Ray analysis in space telescopesCode1
AD-LLM: Benchmarking Large Language Models for Anomaly DetectionCode1
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural NetworksCode1
Deep Isolation Forest for Anomaly DetectionCode1
Deep Learning for Time Series Anomaly Detection: A SurveyCode1
Deep Reinforcement Learning for Cost-Effective Medical DiagnosisCode1
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly DetectionCode1
A Discrepancy Aware Framework for Robust Anomaly DetectionCode1
AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly DetectionCode1
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile RobotsCode1
Deep Graph-level Anomaly Detection by Glocal Knowledge DistillationCode1
ADGym: Design Choices for Deep Anomaly DetectionCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
ADformer: A Multi-Granularity Transformer for EEG-Based Alzheimer's Disease AssessmentCode1
Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive LearningCode1
Deep Generative Classification of Blood Cell MorphologyCode1
Deep Orthogonal Hypersphere Compression for Anomaly DetectionCode1
Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly DataCode1
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly DetectionCode1
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly DetectionCode1
Deep Contrastive One-Class Time Series Anomaly DetectionCode1
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition SoundsCode1
Deep Anomaly Detection Using Geometric TransformationsCode1
Anomaly Detection with Score Distribution DiscriminationCode1
Deep Anomaly Detection with Outlier ExposureCode1
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language ModelsCode1
GLAD: Content-aware Dynamic Graphs For Log Anomaly DetectionCode1
Deep Anomaly Detection on Attributed NetworksCode1
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly DetectionCode1
Deep Dual Support Vector Data Description for Anomaly Detection on Attributed NetworksCode1
DATE: Detecting Anomalies in Text via Self-Supervision of TransformersCode1
Anomaly Detection in Medical Imaging with Deep Perceptual AutoencodersCode1
DAGAD: Data Augmentation for Graph Anomaly DetectionCode1
DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly DetectionCode1
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security ApplicationsCode1
CutPaste: Self-Supervised Learning for Anomaly Detection and LocalizationCode1
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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