2025/11/20 by Qing Zhang, Zhang, Qing, Jing Huang +5
Computer Science · Psychology · #Artificial Intelligence in Games #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Human-Computer Interaction (cs.HC) #Social Robot Interaction and HRI
paper · pdf · doi:10.48550/arxiv.2511.16038
openalex publication_date 2025/11/20 · openalex created_date 2025/11/23 · openalex updated_date 2026/07/28
Current text-to-image models struggle to render the nuanced facial expressions required for compelling manga narratives, largely due to the ambiguity of language itself. To bridge this gap, we introduce an interactive system built on a novel, dual-hybrid pipeline. The first stage combines landmark-based auto-detection with a manual framing tool for robust, artist-centric face preparation. The second stage maps expressions using the LivePortrait engine, blending intuitive performative input from video for fine-grained control. Our case study analysis suggests that this integrated workflow can streamline the creative process and effectively translate narrative intent into visual expression. This work presents a practical model for human-AI co-creation, offering artists a more direct and intuitive means of ``infusing souls'' into their characters. Our primary contribution is not a new generative model, but a novel, interactive workflow that bridges the gap between artistic intent and AI execution.