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 451–500 of 4856 papers

TitleStatusHype
Using Causality for Enhanced Prediction of Web Traffic Time Series—0
Predictive modeling and anomaly detection in large-scale web portals through the CAWAL framework—0
An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus—0
Synthetic User Behavior Sequence Generation with Large Language Models for Smart Homes—0
DINAMO: Dynamic and INterpretable Anomaly MOnitoring for Large-Scale Particle Physics ExperimentsCode0
Battery State of Health Estimation Using LLM Framework—0
GDformer: Going Beyond Subsequence Isolation for Multivariate Time Series Anomaly DetectionCode0
Real-Time Anomaly Detection with Synthetic Anomaly Monitoring (SAM)—0
KoopAGRU: A Koopman-based Anomaly Detection in Time-Series using Gated Recurrent Units—0
Detecting Anomalies Using Rotated Isolation Forest—0
si4onnx: A Python package for Selective Inference in Deep Learning Models—0
Anomaly Detection in Cooperative Vehicle Perception Systems under Imperfect CommunicationCode0
Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems—0
MAUCell: An Adaptive Multi-Attention Framework for Video Frame Prediction—0
Enhancing Web Service Anomaly Detection via Fine-grained Multi-modal Association and Frequency Domain Analysis—0
LLM Assisted Anomaly Detection Service for Site Reliability Engineers: Enhancing Cloud Infrastructure Resilience—0
Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?—0
Large Models in Dialogue for Active Perception and Anomaly DetectionCode0
Addressing Out-of-Label Hazard Detection in Dashcam Videos: Insights from the COOOL ChallengeCode0
Mitigating Spurious Negative Pairs for Robust Industrial Anomaly DetectionCode0
A Transfer Learning Framework for Anomaly Detection in Multivariate IoT Traffic Data—0
Efficient Client Selection in Federated Learning—0
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
Median of Forests for Robust Density Estimation—0
Semi-supervised Anomaly Detection with Extremely Limited Labels in Dynamic Graphs—0
Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector—0
Kernel-Based Anomaly Detection Using Generalized Hyperbolic ProcessesCode0
"Stones from Other Hills can Polish Jade": Zero-shot Anomaly Image Synthesis via Cross-domain Anomaly Injection—0
Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case—0
Bi-directional Curriculum Learning for Graph Anomaly Detection: Dual Focus on Homogeneity and Heterogeneity—0
Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models—0
Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly DetectionCode0
Leveraging Digital Twin and Machine Learning Techniques for Anomaly Detection in Power Electronics Dominated Grid—0
Unraveling Normal Anatomy via Fluid-Driven Anomaly RandomizationCode1
GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality—0
Autoencoders for Anomaly Detection are Unreliable—0
Anomaly Detection in Double-entry Bookkeeping Data by Federated Learning System with Non-model Sharing Approach—0
Towards Accurate Unified Anomaly SegmentationCode1
Beyond Window-Based Detection: A Graph-Centric Framework for Discrete Log Anomaly Detection—0
Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment LabelsCode1
Score Combining for Contrastive OOD Detection—0
TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection—0
Teacher Encoder-Student Decoder Denoising Guided Segmentation Network for Anomaly Detection—0
Anomaly Detection for Industrial Applications, Its Challenges, Solutions, and Future Directions: A Review—0
A Survey of World Models for Autonomous DrivingCode1
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model—0
A Survey on Diffusion Models for Anomaly DetectionCode2
FiLo++: Zero-/Few-Shot Anomaly Detection by Fused Fine-Grained Descriptions and Deformable LocalizationCode2
ComplexVAD: Detecting Interaction Anomalies in Video—0
Sequential PatchCore: Anomaly Detection for Surface Inspection using Synthetic Impurities—0
Show:102550
← PrevPage 10 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