从风格复制到风格探索：借助分析-实验-重定位框架实现艺术风格探索
From Style Replication to Style Exploration: Enabling Art Style Exploration with Analyze-Experiment-Resituate Framework
- National Taiwan University（台湾大学）
- University of Tsukuba（筑波大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
该研究针对现有生成式AI工具在艺术风格探索上的不足，提出AER框架，经原型系统及对照、实地研究验证，可提升艺术家风格探索的自主性与反思性，为未来艺术辅助工具设计提供启示。
AI中文摘要：
艺术风格是专业数字艺术家的标志，通过反复实验、反思与调整发展而成。尽管生成式人工智能（GenAI）能高保真地复制风格，但现有工具对探索新风格方向的支持有限，且可能鼓励风格复制而非探索。为解决这一差距，我们基于对10位专业数字艺术家的访谈，提出了分析-实验-重定位（Analyze-Experiment-Resituate，AER）框架，用于AI辅助的风格探索。AER不优先仅关注视觉吸引力输出，而是支持风格探索的三项核心实践：解读参考作品、尝试风格可能性、反思新兴风格可能获得的反馈。具体而言，AER使艺术家能够：（1）将艺术作品分解为可解释的风格元素；（2）基于自身选择进行可控实验；（3）通过模拟社会视角重定位新兴风格。我们将AER实现为原型系统，并对16位艺术家开展对照研究进行评估。与直接风格迁移工作流相比，AER提升了艺术家在探索新风格方向时的自主性与反思性。对4位艺术家开展的为期两周的实地研究，揭示了AER框架如何影响日常风格探索，如各阶段的反思、实验及风格决策。我们讨论了设计AI辅助风格探索工作流的机遇与挑战，并概述了未来艺术辅助工具的启示。
英文摘要：
Art style is a signature of professional digital artists that develops through repeated experimentation, reflection, and adaptation. While generative AI (GenAI) can reproduce styles with high fidelity, current tools provide limited support for exploring new stylistic directions and may encourage style replication over exploration. To address this gap, we propose Analyze-Experiment-Resituate (AER), a framework for AI-assisted style exploration derived from interviews with 10 professional digital artists. Rather than prioritizing visually appealing outputs alone, AER supports three core practices of style exploration, including interpreting references, trying out stylistic possibilities, and reflecting on how emerging styles may be received. Specifically, AER enabled artists to (1) analyze artworks into interpretable stylistic elements, (2) have controllable experimentation guided by their own choices, and (3) resituate emerging styles through simulated social perspectives. We implemented AER in a prototype system and evaluated it in a controlled study with 16 artists. Compared with a direct style-transfer workflow, AER increased artists' agency and reflection as they pursued new stylistic directions. A two-week field study with four artists revealed how the AER framework influenced daily style exploration, such as reflection, experimentation, and stylistic decision-making at each stage. We discuss opportunities and challenges in designing AI-assisted style-exploration workflows, and outline implications for future artistic support tools.
