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SOTA
Détection d'anomalie
Anomaly Detection On Fashion Mnist
Anomaly Detection On Fashion Mnist
Métriques
ROC AUC
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
ROC AUC
Paper Title
Repository
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
-
IGD (scratch)
92.01
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
GAN based Anomaly Detection in Imbalance Problems
98.6
GAN-based Anomaly Detection in Imbalance Problems
-
Shell-based Anomaly (supervised)
92.1
Shell Theory: A Statistical Model of Reality
IGD (pre-trained ImageNet)
93.57
Deep One-Class Classification via Interpolated Gaussian Descriptor
PANDA-OE
91.8
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
Reverse Distillation
95.0
Anomaly Detection via Reverse Distillation from One-Class Embedding
PANDA
95.6
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
IGD (pre-trained SSL)
94.41
Deep One-Class Classification via Interpolated Gaussian Descriptor
DASVDD
92.6
DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection
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