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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 151–200 of 4856 papers

TitleStatusHype
Anomaly Transformer: Time Series Anomaly Detection with Association DiscrepancyCode2
Tribuo: Machine Learning with Provenance in JavaCode2
Towards Total Recall in Industrial Anomaly DetectionCode2
Is Space-Time Attention All You Need for Video Understanding?Code2
TadGAN: Time Series Anomaly Detection Using Generative Adversarial NetworksCode2
Self-Supervised Log ParsingCode2
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic ThresholdingCode2
Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web ApplicationsCode2
A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational AutoencoderCode2
LSTM-based Encoder-Decoder for Multi-sensor Anomaly DetectionCode2
Sequential keypoint density estimator: an overlooked baseline of skeleton-based video anomaly detectionCode1
SmartHome-Bench: A Comprehensive Benchmark for Video Anomaly Detection in Smart Homes Using Multi-Modal Large Language ModelsCode1
Probing Deep into Temporal Profile Makes the Infrared Small Target Detector Much BetterCode1
Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive MappingCode1
Diffusion-Based Electrocardiography Noise Quantification via Anomaly DetectionCode1
Self-supervised Learning of Echocardiographic Video Representations via Online Cluster DistillationCode1
PatchGuard: Adversarially Robust Anomaly Detection and Localization through Vision Transformers and Pseudo AnomaliesCode1
FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series ClassificationCode1
RoBiS: Robust Binary Segmentation for High-Resolution Industrial ImagesCode1
Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-ThoughtCode1
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly DetectionCode1
Online Isolation ForestCode1
Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly DetectionCode1
SpectrumFM: A Foundation Model for Intelligent Spectrum ManagementCode1
VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video UnderstandingCode1
Search is All You Need for Few-shot Anomaly DetectionCode1
AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly DetectionCode1
Crane: Context-Guided Prompt Learning and Attention Refinement for Zero-Shot Anomaly DetectionsCode1
SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical ImagingCode1
Reconstruction-Free Anomaly Detection with Diffusion Models via Direct Latent Likelihood EvaluationCode1
System Log Parsing with Large Language Models: A ReviewCode1
Multi-Flow: Multi-View-Enriched Normalizing Flows for Industrial Anomaly DetectionCode1
TailedCore: Few-Shot Sampling for Unsupervised Long-Tail Noisy Anomaly DetectionCode1
Omni-AD: Learning to Reconstruct Global and Local Features for Multi-class Anomaly DetectionCode1
The MVTec AD 2 Dataset: Advanced Scenarios for Unsupervised Anomaly DetectionCode1
VADMamba: Exploring State Space Models for Fast Video Anomaly DetectionCode1
UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural NetworksCode1
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR DataCode1
STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive ApplicationsCode1
Learning Decision Trees as Amortized Structure InferenceCode1
Can Multimodal LLMs Perform Time Series Anomaly Detection?Code1
MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly DetectionCode1
Positional Encoding in Transformer-Based Time Series Models: A SurveyCode1
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly DetectionCode1
Out-of-Distribution Detection on Graphs: A SurveyCode1
MAAT: Mamba Adaptive Anomaly Transformer with association discrepancy for time seriesCode1
SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited LabelsCode1
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
Unraveling Normal Anatomy via Fluid-Driven Anomaly RandomizationCode1
Towards Accurate Unified Anomaly SegmentationCode1
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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