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 501525 of 4856 papers

TitleStatusHype
FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language ModelCode1
Anomaly Detection for Solder Joints Using β-VAECode1
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier ImagesCode1
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly DetectionCode1
Diversity-Measurable Anomaly DetectionCode1
MDF-Net for abnormality detection by fusing X-rays with clinical dataCode1
Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution DetectionCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous DrivingCode1
A Principled Approach to Enriching Security-related Data for Running Processes through Statistics and Natural Language ProcessingCode1
Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly LocalizationCode1
Alleviating Structural Distribution Shift in Graph Anomaly DetectionCode1
Exploring Pose-Based Anomaly Detection for Retail Security: A Real-World Shoplifting Dataset and BenchmarkCode1
Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale LearningCode1
Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography ImagesCode1
Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly DetectionCode1
GPT-4V-AD: Exploring Grounding Potential of VQA-oriented GPT-4V for Zero-shot Anomaly DetectionCode1
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR DataCode1
A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data StreamsCode1
Explaining Anomalies Detected by Autoencoders Using SHAPCode1
Exploring Image Augmentations for Siamese Representation Learning with Chest X-RaysCode1
Explainable Time Series Anomaly Detection using Masked Latent Generative ModelingCode1
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile RobotsCode1
Explainable Deep Few-shot Anomaly Detection with Deviation NetworksCode1
AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-DecoderCode1
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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