论文标题
共同创造设计的协作，互动和上下文感知的绘图代理
A Collaborative, Interactive and Context-Aware Drawing Agent for Co-Creative Design
论文作者
论文摘要
文本条件生成模型的最新进展为我们提供了能够创造出惊人质量图像的神经网络，无论它们是现实，抽象甚至创造性的。这些模型的共同点（或多或少是明确的），它们都旨在在某些条件下产生高质量的一次性输出，并且因为它们不适合创意协作框架。利用认知科学的理论来模拟专业设计师和艺术家的想法，我们认为这种设置与前者和引入CICADA的不同：一种协作，互动的上下文感知绘图剂。 CICADA使用基于矢量的综合方法逐量化方法来绘制部分草图（例如用户可能提供的），并通过添加和/或明智地修改轨迹来将其发展为目标。鉴于几乎没有探索这个主题，我们还通过提出多样性度量来评估模型的所需特征来评估模型的所需特征。证明CICADA可以产生与人类用户相当的质量草图，增强的多样性，最重要的是能够通过以灵活的方式继续思考用户的贡献来应对变化。
Recent advances in text-conditioned generative models have provided us with neural networks capable of creating images of astonishing quality, be they realistic, abstract, or even creative. These models have in common that (more or less explicitly) they all aim to produce a high-quality one-off output given certain conditions, and in that they are not well suited for a creative collaboration framework. Drawing on theories from cognitive science that model how professional designers and artists think, we argue how this setting differs from the former and introduce CICADA: a Collaborative, Interactive Context-Aware Drawing Agent. CICADA uses a vector-based synthesis-by-optimisation method to take a partial sketch (such as might be provided by a user) and develop it towards a goal by adding and/or sensibly modifying traces. Given that this topic has been scarcely explored, we also introduce a way to evaluate desired characteristics of a model in this context by means of proposing a diversity measure. CICADA is shown to produce sketches of quality comparable to a human user's, enhanced diversity and most importantly to be able to cope with change by continuing the sketch minding the user's contributions in a flexible manner.
