Anomaly Detection On One Class Imagenet 30

AUROC

평가 결과

이 벤치마크에서 각 모델의 성능 결과

비교 표

모델 이름	AUROC
using-self-supervised-learning-can-improve	77.9
using-self-supervised-learning-can-improve	84.8
using-self-supervised-learning-can-improve	65.3
csi-novelty-detection-via-contrastive	91.6
using-self-supervised-learning-can-improve	85.7
explainable-deep-one-class-classification	91
exposing-outlier-exposure-what-can-be-learned	99.88
exposing-outlier-exposure-what-can-be-learned	99.90
using-self-supervised-learning-can-improve	81.6
using-self-supervised-learning-can-improve	56.1
exposing-outlier-exposure-what-can-be-learned	97.7