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19 April 2024 |
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Article overview
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A Deep Factorization of Style and Structure in Fonts | | Akshay Srivatsan
; Jonathan T. Barron
; Dan Klein
; Taylor Berg-Kirkpatrick
; | | Date: |
2 Oct 2019 | | Abstract: | We propose a deep factorization model for typographic analysis that
disentangles content from style. Specifically, a variational inference
procedure factors each training glyph into the combination of a
character-specific content embedding and a latent font-specific style variable.
The underlying generative model combines these factors through an asymmetric
transpose convolutional process to generate the image of the glyph itself. When
trained on corpora of fonts, our model learns a manifold over font styles that
can be used to analyze or reconstruct new, unseen fonts. On the task of
reconstructing missing glyphs from an unknown font given only a small number of
observations, our model outperforms both a strong nearest neighbors baseline
and a state-of-the-art discriminative model from prior work. | | Source: | arXiv, 1910.0748 | | Services: | Forum | Review | PDF | Favorites | |
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