Generative Models

Attribute2Font

Introduced by Wang et al. in Attribute2Font: Creating Fonts You Want From Attributes

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

Source: Attribute2Font: Creating Fonts You Want From Attributes

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Font Style Transfer 1 50.00%
Style Transfer 1 50.00%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

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