发表机构
MIT Media Lab; MIT（麻省理工学院媒体实验室; 麻省理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过EmoToon探针探索人机协作在情感驱动漫画分镜中的作用，发现AI辅助提升情感表达与美学质量但降低创作所有权，强调平衡输出质量与用户自由。
AI 中文摘要
虽然生成式AI模型能够产生视觉上忠实的艺术作品，但它们往往在传达情感真实性方面有所欠缺——而情感真实性是人类表达的关键驱动力。在视觉叙事中，尤其是漫画分镜中，这一差距变得尤为显著：有效的分镜需要技术知识（如解剖学准确性或场景构图）和情感洞察力（来自生活经验）。我们探索人机协作如何支持情感驱动的创造力，其中用户的感受引导生成，情感共鸣是目标。我们提出了EmoToon，一个技术探针，帮助非专业艺术家生成草图风格的分镜并迭代视觉想法。在一项N=25名参与者的对照研究中，我们发现AI辅助显著改善了情感表达、美学质量和探索性，但降低了用户的创作所有权。我们的发现为漫画叙事领域的人机共创提供了更广泛的见解，强调了输出质量与用户自由之间的平衡，并为该领域的图像生成模型提出了新的挑战。
英文摘要
While generative AI models can produce visually faithful artwork, they often fall short in conveying emotional authenticity--a key driver of human expression. In visual storytelling, particularly comic storyboarding, this gap becomes pronounced: effective storyboards require both technical knowledge (e.g., anatomical accuracy or scenic composition) and emotional insight (from lived experience). We explore how human-AI collaboration can support emotion-driven creativity, where the user's feelings guide generation and emotional resonance is the goal. We present EmoToon, a technology probe that helps non-professional artists generate sketch-like storyboards and iterate on visual ideas. In a controlled study with N=25 participants, we find that AI assistance significantly improves emotional expression, aesthetic quality, and exploration, but reduces users' creative ownership. Our findings offer broader insights for human-AI co-creation in the domain of comic storytelling, emphasizing balance between output quality and user freedom, and raising new challenges for image generation models in this domain.
CommentsCopyright protected by IEEE, 10 pages, 6 figures, 2 tables, in proceedings of 14th International Conference on Affective Computing and Intelligent Interaction (ACII 2026)
