ArtTypo: Multi-Level Controlled Artistic Typography with Iterative Feedback

Kaiyue Liu, Lei Wu, Mingzhe Yu, Xiaole Liu, Yajie Xu, Xiangxu Meng

Abstract: Artistic typography visualizes the meaning of input characters by harmonizing font and imagery. However, current methods face significant challenges in balancing artistic expression with readability, precise control, and with limited support for non-Latin scripts. To address these issues, we propose ArtTypo, a novel multimodal guided, multi-level controlled framework for artistic typography with iterative feedback. To improve artistic expression, we follow the principles of art design, implement a Chain-of-Thought approach through Multimodal Large Language Models to integrate user intentions, and a feedback module for iterative refinement of outputs. For precise and multi-level control, we introduce auto path match to extract vector paths aligned with multimodal input. Additionally, we develop a texture with background preserving diffusion process, ensuring clean outputs and artistic expression as well. Experiments demonstrate that ArtTypo effectively generates diverse artistic typography, consistently producing visually appealing and contextually sensitive results.

External IDs:dblp:conf/icmcs/LiuWYLXM25