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 38513875 of 4856 papers

TitleStatusHype
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection0
Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device FailureCode1
Anomaly Detection-Based Unknown Face Presentation Attack DetectionCode1
ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection0
Learning Retrospective Knowledge with Reverse Reinforcement Learning0
Brain Tumor Anomaly Detection via Latent Regularized Adversarial Network0
Artificial Intelligence and Machine Learning in 5G Network Security: Opportunities, advantages, and future research trends0
Meta-Learning for One-Class Classification with Few Examples using Order-Equivariant NetworkCode0
Few-Shot One-Class Classification via Meta-LearningCode1
Deep Learning for Anomaly Detection: A Review0
Explainable Deep One-Class ClassificationCode1
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-DecodingCode0
Deep Learning Models for Visual Inspection on Automotive Assembling Line0
Laplacian Change Point Detection for Dynamic GraphsCode1
Subject-Aware Contrastive Learning for BiosignalsCode1
Feature Extraction for Novelty Detection in Network Traffic0
Random Partitioning Forest for Point-Wise and Collective Anomaly Detection -- Application to Intrusion DetectionCode1
Patch SVDD: Patch-level SVDD for Anomaly Detection and SegmentationCode1
Abnormal activity capture from passenger flow of elevator based on unsupervised learning and fine-grained multi-label recognition0
Generative Damage Learning for Concrete Aging Detection using Auto-flight Images0
Leveraging Siamese Networks for One-Shot Intrusion Detection Model0
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
An Investigation of Traffic Density Changes inside Wuhan during the COVID-19 Epidemic with GF-2 Time-Series Images0
Few-Shot Anomaly Detection for Polyp Frames from ColonoscopyCode1
Anomaly Detection using Deep Reconstruction and Forecasting for Autonomous Systems0
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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