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Actively acquiring reference glyphs can dramatically enhance few-shot font generation quality while minimizing the number of queries to designers.
Class-imbalanced semi-supervised learning gets a boost from Proportion Loss, a simple regularization term that aligns model predictions with the global class distribution, outperforming existing methods on Long-tailed CIFAR-10.
