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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–300 of 4856 papers

TitleStatusHype
Foundation Models for Time Series: A Survey—0
Overcoming the Identity Mapping Problem in Self-Supervised Hyperspectral Anomaly DetectionCode0
AttackLLM: LLM-based Attack Pattern Generation for an Industrial Control System—0
Multi-Flow: Multi-View-Enriched Normalizing Flows for Industrial Anomaly DetectionCode1
Pyramid-based Mamba Multi-class Unsupervised Anomaly DetectionCode0
Anomaly Detection in Time Series Data Using Reinforcement Learning, Variational Autoencoder, and Active Learning—0
Analytical Discovery of Manifold with Machine Learning—0
Beyond Conventional Transformers: The Medical X-ray Attention (MXA) Block for Improved Multi-Label Diagnosis Using Knowledge DistillationCode0
CRC-SGAD: Conformal Risk Control for Supervised Graph Anomaly Detection—0
VISTA: Unsupervised 2D Temporal Dependency Representations for Time Series Anomaly Detection—0
Improving log-based anomaly detection through learned adaptive filter—0
ZClip: Adaptive Spike Mitigation for LLM Pre-TrainingCode2
TailedCore: Few-Shot Sampling for Unsupervised Long-Tail Noisy Anomaly DetectionCode1
Fault injection analysis of Real NVP normalising flow model for satellite anomaly detection—0
What is AI, what is it not, how we use it in physics and how it impacts... you—0
Anomaly Detection for Hybrid Butterfly Subspecies via Probability FilteringCode0
Unleashing the Power of Pre-trained Encoders for Universal Adversarial Attack Detection—0
Integrating Quantum-Classical Attention in Patch Transformers for Enhanced Time Series ForecastingCode0
Enhancing Time Series Forecasting with Fuzzy Attention-Integrated TransformersCode0
GAL-MAD: Towards Explainable Anomaly Detection in Microservice Applications Using Graph Attention Networks—0
Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip StatisticsCode0
Federated Structured Sparse PCA for Anomaly Detection in IoT Networks—0
Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly DetectionCode0
Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous DomainsCode0
A Dataset for Semantic Segmentation in the Presence of Unknowns—0
iMedImage Technical Report—0
AssistPDA: An Online Video Surveillance Assistant for Video Anomaly Prediction, Detection, and Analysis—0
VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic FaithfulnessCode5
Omni-AD: Learning to Reconstruct Global and Local Features for Multi-class Anomaly DetectionCode1
VADMamba: Exploring State Space Models for Fast Video Anomaly DetectionCode1
The MVTec AD 2 Dataset: Advanced Scenarios for Unsupervised Anomaly DetectionCode1
Adaptive State-Space Mamba for Real-Time Sensor Data Anomaly Detection—0
Channel impulse response peak clustering using neural networks—0
Refining Time Series Anomaly Detectors using Large Language Models—0
LogicQA: Logical Anomaly Detection with Vision Language Model Generated Questions—0
β-GNN: A Robust Ensemble Approach Against Graph Structure PerturbationCode0
Post-Hoc Calibrated Anomaly Detection—0
Social Network User Profiling for Anomaly Detection Based on Graph Neural Networks—0
Correcting Deviations from Normality: A Reformulated Diffusion Model for Multi-Class Unsupervised Anomaly DetectionCode2
Anomaly Detection Using Computer Vision: A Comparative Analysis of Class Distinction and Performance Metrics—0
Risk-Based Thresholding for Reliable Anomaly Detection in Concentrated Solar Power Plants—0
Towards Training-free Anomaly Detection with Vision and Language Foundation ModelsCode2
RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated DataCode0
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos—0
Anomize: Better Open Vocabulary Video Anomaly Detection—0
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space ModelCode0
Anomaly Detection and Localization for Speech Deepfakes via Feature Pyramid Matching—0
Assessing workflow impact and clinical utility of AI-assisted brain aneurysm detection: a multi-reader study—0
TRACE: Time SeRies PArameter EffiCient FinE-tuning—0
CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series—0
Show:102550
← PrevPage 6 of 98Next →
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