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 1101–1150 of 4856 papers

TitleStatusHype
M^2AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated ThresholdingCode0
Memory-Augmented Dual-Decoder Networks for Multi-Class Unsupervised Anomaly Detection—0
Advancing Video Anomaly Detection: A Bi-Directional Hybrid Framework for Enhanced Single- and Multi-Task Approaches—0
Uncovering Issues in the Radio Access Network by Looking at the Neighbors—0
Balancing Privacy and Action Performance: A Penalty-Driven Approach to Image Anonymization—0
Pets: General Pattern Assisted Architecture For Time Series Analysis—0
Towards Anomaly-Aware Pre-Training and Fine-Tuning for Graph Anomaly Detection—0
DConAD: A Differencing-based Contrastive Representation Learning Framework for Time Series Anomaly DetectionCode0
Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection—0
Enhancing Pothole Detection and Characterization: Integrated Segmentation and Depth Estimation in Road Anomaly Systems—0
Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving SafetyCode0
Chain-of-Thought Textual Reasoning for Few-shot Temporal Action Localization—0
Can Local Representation Alignment RNNs Solve Temporal Tasks?—0
Quorum: Zero-Training Unsupervised Anomaly Detection using Quantum AutoencodersCode0
Sliced-Wasserstein Distance-based Data Selection—0
MathPhys-Guided Coarse-to-Fine Anomaly Synthesis with SQE-Driven Bi-Level Optimization for Anomaly Detection—0
Predicting BVD Re-emergence in Irish Cattle From Highly Imbalanced Herd-Level Data Using Machine Learning Algorithms—0
3D-PNAS: 3D Industrial Surface Anomaly Synthesis with Perlin Noise—0
LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection—0
EventVAD: Training-Free Event-Aware Video Anomaly Detection—0
HSS-IAD: A Heterogeneous Same-Sort Industrial Anomaly Detection DatasetCode0
ACMamba: Fast Unsupervised Anomaly Detection via An Asymmetrical Consensus State Space Model—0
AFiRe: Anatomy-Driven Self-Supervised Learning for Fine-Grained Representation in Radiographic ImagesCode0
Strengthening Anomaly Awareness—0
A real-time anomaly detection method for robots based on a flexible and sparse latent spaceCode0
SlowFastVAD: Video Anomaly Detection via Integrating Simple Detector and RAG-Enhanced Vision-Language Model—0
Ising Models with Hidden Markov Structure: Applications to Probabilistic Inference in Machine Learning—0
Leveraging Large Self-Supervised Time-Series Models for Transferable Diagnosis in Cross-Aircraft Type Bleed Air System—0
PatchTrAD: A Patch-Based Transformer focusing on Patch-Wise Reconstruction Error for Time Series Anomaly Detection—0
PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization—0
Patch distribution modeling framework adaptive cosine estimator (PaDiM-ACE) for anomaly detection and localization in synthetic aperture radar imageryCode0
Estimation of Solar Spectral Irradiance Using Meteorological Data and Analysis of Optimal Conditions for Solar Power Generation—0
Benchmarking Suite for Synthetic Aperture Radar Imagery Anomaly Detection (SARIAD) AlgorithmsCode0
MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning—0
AMAD: AutoMasked Attention for Unsupervised Multivariate Time Series Anomaly Detection—0
Autoencoder-Based Detection of Anomalous Stokes V Spectra in the Flare-Producing Active Region 13663 Using Hinode/SP Observations—0
A Self-Supervised Framework for Space Object Behaviour Characterisation—0
Hybrid Temporal Differential Consistency Autoencoder for Efficient and Sustainable Anomaly Detection in Cyber-Physical Systems—0
Towards Efficient Real-Time Video Motion Transfer via Generative Time Series Modeling—0
On multipolar magnetic anomaly detection: multipolar signal subspaces, an analytical orthonormal basis, multipolar truncature and detection performance—0
iADCPS: Time Series Anomaly Detection for Evolving Cyber-physical Systems via Incremental Meta-learning—0
AttackLLM: LLM-based Attack Pattern Generation for an Industrial Control System—0
Foundation Models for Time Series: A Survey—0
Overcoming the Identity Mapping Problem in Self-Supervised Hyperspectral Anomaly DetectionCode0
Pyramid-based Mamba Multi-class Unsupervised Anomaly DetectionCode0
Improving log-based anomaly detection through learned adaptive filter—0
Analytical Discovery of Manifold with Machine Learning—0
VISTA: Unsupervised 2D Temporal Dependency Representations for Time Series Anomaly Detection—0
Anomaly Detection in Time Series Data Using Reinforcement Learning, Variational Autoencoder, and Active Learning—0
CRC-SGAD: Conformal Risk Control for Supervised Graph Anomaly Detection—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
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