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Anomaly Detection on Fashion-MNIST (one vs. rest)

Anomaly Detection on Fashion-MNIST (one vs. rest)

94.7Mean AUCBCE-CL

Updated 8mo ago

Evaluation results

Method	Links
BCE-CL2022.05		94.7
CLIP2022.05		89

State-of-the-art paper

BCE-CL

Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images

Dataset

Fashion MNIST

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Related benchmarks

Anomaly Detection on CIFAR-10 one vs. rest 80MTI as OE Anomaly Detection on ImageNet-30 22K as OE (one vs. rest)Anomaly Detection on CUB (one vs. rest)Anomaly Detection on DTD (one vs. rest)Anomaly Detection on ImageNet-30 (one vs. rest)

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