QT-Font: High-efficiency Font Synthesis via Quadtree-based Diffusion Models

Few-shot font generation (FFG) aims to streamline the manual aspects of the font design process. Existing models are capable of generating glyph images in the same style of a few input reference glyphs. However, mainly due to their inefficient glyph representations, these existing FFG methods are limited to generating low-resolution glyph images. To address this problem, we introduce QT-Font, an efficient quadtree-based diffusion model specifically designed for FFG. More specifically, we design a sparse quadtree-based glyph representation to reduce the complexity of the representation space, exhibiting linear complexity and uniqueness. Concurrently, to reduce computational complexity, we propose a U-net model based on the dual quadtree graph network and the discrete diffusion model. Furthermore, a content-aware pooling module is also adopted to lessen the computational demands of the diffusion process. Qualitative and quantitative experiments have been conducted to demonstrate that our QT-Font, compared to existing approaches, can generate high-resolution glyph images with superior quality and more visually pleasing details, meanwhile significantly reducing both parameter sizes and computational costs.