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Pseudo Labels for Single Positive Multi-Label Learning
Then, we treat the teacher model's predictions on the training data as ground-truth labels to train a student network on fully-labeled images.
Understanding Label Bias in Single Positive Multi-Label Learning
Annotating data for multi-label classification is prohibitively expensive because every category of interest must be confirmed to be present or absent.
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