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SotA/Methodology/Anomaly Detection/Fashion-MNIST

Anomaly Detection on Fashion-MNIST

Metric: ROC AUC (higher is better)

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#Model↕ROC AUC▼AugmentationsPaperDate↕Code
1GAN based Anomaly Detection in Imbalance Problems98.6No---
2PANDA95.6NoPANDA: Adapting Pretrained Features for Anomaly ...2020-10-12Code
3Reverse Distillation95NoAnomaly Detection via Reverse Distillation from ...2022-01-26Code
4IGD (pre-trained SSL)94.41NoDeep One-Class Classification via Interpolated G...2021-01-25Code
5IGD (pre-trained ImageNet)93.57NoDeep One-Class Classification via Interpolated G...2021-01-25Code
6Self-Supervised One-class SVM, RBF kernel92.8NoPANDA: Adapting Pretrained Features for Anomaly ...2020-10-12Code
7DASVDD92.6NoDASVDD: Deep Autoencoding Support Vector Data De...2021-06-09Code
8Shell-based Anomaly (supervised)92.1No--Code
9IGD (scratch)92.01NoDeep One-Class Classification via Interpolated G...2021-01-25Code
10PANDA-OE91.8NoPANDA: Adapting Pretrained Features for Anomaly ...2020-10-12Code
11Self-Supervised DeepSVDD84.8NoPANDA: Adapting Pretrained Features for Anomaly ...2020-10-12Code
12P-KDGAN0.9293NoP-KDGAN: Progressive Knowledge Distillation with...2020-07-14-