通过草图和注释增强生成式AI图像细化：多模态提示的比较研究
Enhancing Generative AI Image Refinement with Scribbles and Annotations: A Comparative Study of Multimodal Prompts
AI总结：
本研究通过比较多模态提示，探讨草图和注释如何提升生成式AI图像细化，提出原型并揭示设计师在多模态策略中的偏好。
摘要：
生成式AI（GenAI）图像工具在设计实践中日益被使用，能够快速产生创意，但在调整布局、比例或视觉属性等细化任务上支持有限。虽然文本提示和修补允许局部编辑，但往往在精确、上下文相关和迭代细化方面效率低下或模糊，这促使探索替代方法。本研究探讨了基于笔的草图和注释如何增强GenAI图像细化。与七名专业设计师进行的形式化研究指导了一个原型，支持三种输入模式：纯文本、纯视觉和结合提示。30名设计师和设计学生进行的内组研究比较了这些模式在封闭和开放任务中的表现，评估了表达性、效率、工作负荷、用户体验、迭代和多模态策略。视觉提示提高了空间编辑的清晰度和速度，减少了工作负荷，而文本仍有效用于语义和全局变化。结合模式获得了最高总体评分，使互补使用成为可能，平衡了空间精度与语义细节，并支持更流畅的迭代。任务特定的偏好也显现出来：添加新对象通常需要两种模式，而移动或修改元素通常通过视觉输入处理。本研究贡献（1）多模态提示在GenAI细化中的实证比较，（2）集成了草图和注释的原型，以及（3）关于设计师多模态策略的见解，以指导未来GenAI界面，使其更好地支持GenAI支持的设计工作流程中的细化。
英文摘要：
Generative AI (GenAI) image tools are increasingly used in design practice, enabling rapid ideation but offering limited support for refinement tasks such as adjusting layout, scale, or visual attributes. While text prompts and inpainting allow localized edits, they often remain inefficient or ambiguous for precise, in-context, and iterative refinement -- motivating the exploration of alternative methods. This work examines how pen-based scribbles and annotations can enhance GenAI image refinement. A formative study with seven professional designers informed a prototype supporting three input modalities: text-only, visual-only, and combined prompting. A within-subjects study with 30 designers and design students compared these modalities across closed- and open-ended tasks, evaluating expressiveness, efficiency, workload, user experience, iteration, and multimodal strategies. Visual prompts improved clarity and speed for spatial edits while reducing workload, whereas text remained effective for semantic and global changes. The combined modality received the highest overall ratings, enabling complementary use, balancing spatial precision with semantic detail, and supporting smoother iteration. Task-specific preferences also emerged: adding new objects often required both modalities, while moving or modifying elements was typically handled through visual input. This work contributes (1) an empirical comparison of multimodal prompting for GenAI refinement, (2) a prototype integrating scribbles and annotations, and (3) insights into designers' multimodal strategies to inform future GenAI interfaces that better support refinement in GenAI-supported design workflows.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
