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

Showing 15011525 of 4856 papers

TitleStatusHype
Image-based Deep Learning for Smart Digital Twins: a Review0
Distillation-based fabric anomaly detectionCode0
Locally Differentially Private Embedding Models in Distributed Fraud Prevention Systems0
AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low ToleranceCode1
SCALA: Sparsification-based Contrastive Learning for Anomaly Detection on Attributed Networks0
Regression Based Anomaly Detection in Electric Vehicle State of Charge Fluctuations Through Analysis of EVCI Data0
Exploring Hyperspectral Anomaly Detection with Human Vision: A Small Target Aware DetectorCode0
Unsupervised Continual Anomaly Detection with Contrastively-learned PromptCode2
Hyperbolic Anomaly Detection0
Error Detection in Egocentric Procedural Task Videos0
Uncovering What Why and How: A Comprehensive Benchmark for Causation Understanding of Video AnomalyCode2
Prompt-Enhanced Multiple Instance Learning for Weakly Supervised Video Anomaly DetectionCode0
Pre-training Vision Models with Mandelbulb VariationsCode0
Multi-Scale Video Anomaly Detection by Multi-Grained Spatio-Temporal Representation Learning0
Towards Surveillance Video-and-Language Understanding: New Dataset Baselines and Challenges0
A Maritime Industry Experience for Vessel Operational Anomaly Detection: Utilizing Deep Learning Augmented with Lightweight Interpretable Models0
Sensor Data Simulation for Anomaly Detection of the Elderly Living AloneCode0
METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection0
Unsupversied feature correlation model to predict breast abnormal variation maps in longitudinal mammogramsCode0
Temporal Knowledge Distillation for Time-Sensitive Financial Services Applications0
Anticipated Network Surveillance -- An extrapolated study to predict cyber-attacks using Machine Learning and Data Analytics0
Soft Contrastive Learning for Time SeriesCode1
ReSynthDetect: A Fundus Anomaly Detection Network with Reconstruction and Synthetic Features0
Abnormal component analysis0
Generating and Reweighting Dense Contrastive Patterns for Unsupervised Anomaly Detection0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified