4 citations · 9 across the 9 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.CV2021
Few-shot Font Generation with Weakly Supervised Localized Representations
Song Park, Sanghyuk Chun, Junbum Cha +2
Automatic few-shot font generation aims to solve a well-defined, real-world problem because manual font designs are expensive and sensitive to the expertise of designers. Existing…
cs.CV2021★ 3 cited
StyleAugment: Learning Texture De-biased Representations by Style Augmentation without Pre-defined Textures
Sanghyuk Chun, Song Park
Recent powerful vision classifiers are biased towards textures, while shape information is overlooked by the models. A simple attempt by augmenting training images using the artist…
cs.CV2021
Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts
Song Park, Sanghyuk Chun, Junbum Cha +2
A few-shot font generation (FFG) method has to satisfy two objectives: the generated images should preserve the underlying global structure of the target character and present the…