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Anomaly Detection On Hyper Kvasir Dataset

Metrics

AUC

Results

Performance results of various models on this benchmark

Model Name	AUC	Paper Title	Repository
IGD	0.939	Deep One-Class Classification via Interpolated Gaussian Descriptor	-
CCD	0.972	Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images	-
F-Anogan	0.907	f-AnoGAN: Fast Unsupervised Anomaly Detection with Generative Adversarial Networks
OCGAN	0.813	OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations	-
PaDiM	0.923	PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization	-
PANDA	0.937	PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation	-

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Anomaly Detection On Hyper Kvasir Dataset | SOTA | HyperAI