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Anomaly Detection On Fashion Mnist

Metrics

ROC AUC

Results

Performance results of various models on this benchmark

		Paper Title	Repository
GAN based Anomaly Detection in Imbalance Problems	98.6	GAN-based Anomaly Detection in Imbalance Problems	-
PANDA	95.6	PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
Reverse Distillation	95.0	Anomaly Detection via Reverse Distillation from One-Class Embedding
IGD (pre-trained SSL)	94.41	Deep One-Class Classification via Interpolated Gaussian Descriptor
IGD (pre-trained ImageNet)	93.57	Deep One-Class Classification via Interpolated Gaussian Descriptor
Self-Supervised One-class SVM, RBF kernel	92.8	PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
DASVDD	92.6	DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection
Shell-based Anomaly (supervised)	92.1	Shell Theory: A Statistical Model of Reality	-
IGD (scratch)	92.01	Deep One-Class Classification via Interpolated Gaussian Descriptor
PANDA-OE	91.8	PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
Self-Supervised DeepSVDD	84.8	PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
P-KDGAN	0.9293	P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection	-

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Anomaly Detection On Fashion Mnist | SOTA | HyperAI