Yuxin Kong — accepted AI-conference papers

2024

FontDiffuser: One-Shot Font Generation via Denoising Diffusion with Multi-Scale Content Aggregation and Style Contrastive Learning

Zhenhua Yang, Dezhi Peng, Yuxin Kong, Yuyi Zhang, Cong Yao, Lianwen Jin

AAAI 2024technical

Automatic font generation is an imitation task, which aims to create a font library that mimics the style of reference images while preserving the content from source images. Although existing font generation methods have achieved satisfactory performance, they still struggle with complex characters…

Cited by 40 Source ↗PDF ↗code ↗Scholar ↗

2022

Look Closer To Supervise Better: One-Shot Font Generation via Component-Based Discriminator

Yuxin Kong, Canjie Luo, Weihong Ma, Qiyuan Zhu, Shenggao Zhu, Nicholas Yuan +1

CVPR 2022oral

Automatic font generation remains a challenging research issue due to the large amounts of characters with complicated structures. Typically, only a few samples can serve as the style/content reference (termed few-shot learning), which further increases the difficulty to preserve local style pattern…

Cited by 72 PDF ↗code ↗Scholar ↗