Visual communication often needs stylistically consistent icons that span concrete and abstract meanings, for use in diverse contexts. We present Iconix, a human-AI co-creative system that organizes icon generation along two axes: semantic richness (what is depicted) and visual complexity (how much detail). Given a user-specified concept, Iconix constructs a semantic scaffold of related analytical perspectives and employs chained, image-conditioned generation to produce a coherent style of exemplars. Each exemplar is then automatically distilled into a progressive sequence, from detailed and elaborate to abstract and simple. The resulting two-dimensional grid exposes a navigable space, helping designers reason jointly about figurative content and visual abstraction. A within-subjects study (N = 32) found that compared to a baseline workflow, participants produced icon grids more creatively, reported lower workload, and explored a coherent range of design variations. We discuss implications for human-machine co-creative approaches that couple semantic scaffolding with progressive simplification to support visual abstraction.

翻译：视觉传达通常需要风格一致且涵盖具体与抽象含义的图标，以适应多样化的使用场景。本文提出Iconix，一种人机协同创作系统，该系统沿两个维度组织图标生成：语义丰富度（描绘内容）与视觉复杂度（细节程度）。给定用户指定的概念后，Iconix会构建相关分析视角的语义支架，并采用链式图像条件生成技术来产出一系列风格统一的示例图标。每个示例随后被自动提炼为从精细繁复到抽象简约的渐进序列。最终形成的二维网格呈现出一个可导航的创作空间，帮助设计者协同思考具象内容与视觉抽象的关系。一项受试者内研究（N = 32）表明，与基线工作流程相比，参与者创作出的图标网格更具创造性，主观工作负荷更低，并能探索连贯的设计变体范围。本文进一步探讨了将语义支架与渐进简化相结合的人机协同创作方法对视觉抽象支持的意义。