Anomaly Detection On Mnist
Metrics
ROC AUC
Results
Performance results of various models on this benchmark
| Paper Title | ||
|---|---|---|
| GAN-based Anomaly Detection in Imbalance Problems | 99.7 | GAN-based Anomaly Detection in Imbalance Problems |
| IGD (pre-trained ImageNet) | 99.27 | Deep One-Class Classification via Interpolated Gaussian Descriptor |
| IGD (scratch) | 98.69 | Deep One-Class Classification via Interpolated Gaussian Descriptor |
| DASVDD | 97.7 | DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection |
| LIS-AE | 97.68 | Latent-Insensitive autoencoders for Anomaly Detection |
| P-KDGAN | 97.25 | P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection |
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