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Dash: Semi-Supervised Learning with Dynamic Thresholding
In this work we develop a simple yet powerful framework, whose key idea is to select a subset of training examples from the unlabeled data when performing existing SSL methods so that only the unlabeled examples with pseudo labels related to the labeled data will be used to train models.
Learning to Cluster Faces via Transformer
In this paper, we repurpose the well-known Transformer and introduce a Face Transformer for supervised face clustering.
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