المفاهيم الأساسية
FontCLIP connects vision-language models with typographic knowledge, enabling multilingual font retrieval and optimization.
الملخص
Acquiring the desired font for design tasks can be challenging, but FontCLIP bridges semantic understanding with typographic knowledge. It generalizes to different languages and recognizes out-of-domain attributes, simplifying font retrieval and optimization. The model integrates typography-specific knowledge into a vision-language model through finetuning, demonstrating unprecedented abilities in multilingual applications.
FontCLIP's dual-modality enables multilingual font retrieval and letter shape optimization without the need for vector-based font files. The model's generalization capabilities across languages and attributes make it a valuable tool for designers seeking desired fonts efficiently.
الإحصائيات
EUROGRAPHICS 2024 / A. Bermano and E. Kalogerakis (Guest Editors)
Volume 43 (2024), Number 2
200 Roman fonts annotated with 37 attribute scores dataset used for finetuning FontCLIP model.