Methods › Computer Vision › Font Generation Models › Attribute2Font
Attribute2Font
Introduced by Yizhi Wang et al. in Attribute2Font: Creating Fonts You Want From Attributes
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Attribute2Font is a model that automatically creates fonts by synthesizing visually pleasing glyph images according to user-specified attributes and their corresponding values. Specifically, Attribute2Font is trained to perform font style transfer between any two fonts conditioned on their attribute values. After training, the model can generate glyph images in accordance with an arbitrary set of font attribute values. A unit named Attribute Attention Module is designed to make those generated glyph images better embody the prominent font attributes. A semi-supervised learning scheme is also introduced to exploit a large number of unlabeled fonts
Papers archive 2025-07-28
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Attribute2Font: Creating Fonts You Want From Attributes 16 May 2020 · 2 repositories · arXiv:2005.07865
Tasks archive 2025-07-28
3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Attribute | 1 |
| Font Style Transfer | 1 |
| Style Transfer | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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