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Outlier detection by ensembling uncertainty with negative objectness
We therefore reconsider direct prediction of K+1 logits that correspond to K groundtruth classes and one outlier class.
Real time dense anomaly detection by learning on synthetic negative data
Most approaches to dense anomaly detection rely on generative modeling or on discriminative methods that train with negative data.
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