The recent explosion of high-quality image-to-image methods has prompted interest in applying image-to-image methods towards artistic and design tasks. Of interest for architects is to use these methods to generate design proposals from conceptual sketches, usually hand-drawn sketches that are quickly developed and can embody a design intent. More specifically, instantiating a sketch into a visual that can be used to elicit client feedback is typically a time consuming task, and being able to speed up this iteration time is important. While the body of work in generative methods has been impressive, there has been a mismatch between the quality measures used to evaluate the outputs of these systems and the actual expectations of architects. In particular, most recent image-based works place an emphasis on realism of generated images. While important, this is one of several criteria architects look for. In this work, we describe the expectations architects have for design proposals from conceptual sketches, and identify corresponding automated metrics from the literature. We then evaluate several image-to-image generative methods that may address these criteria and examine their performance across these metrics. From these results, we identify certain challenges with hand-drawn conceptual sketches and describe possible future avenues of investigation to address them.

翻译：近年来高质量图像到图像方法的爆发式增长引发了将其应用于艺术与设计任务的兴趣。建筑师关注的是利用这些方法从概念草图（通常是快速绘制且蕴含设计意图的手绘草图）生成设计方案。具体而言，将草图转化为可用于获取客户反馈的可视化内容通常耗时较长，而加快这一迭代过程至关重要。尽管生成方法领域的研究成果令人瞩目，但评估这些系统输出结果的质量标准与建筑师的实际期望之间存在脱节——尤其是当前大多数基于图像的研究过度强调生成图像的逼真度。虽然逼真度很重要，但这仅是建筑师考量的多重标准之一。在本研究中，我们阐述了建筑师对概念草图生成设计方案的期望，并从文献中筛选出对应的自动化评估指标。随后，我们评估了若干可能满足这些标准的图像到图像生成方法，并检验了它们在各指标上的表现。基于这些结果，我们识别出手绘概念草图面临的具体挑战，并描述了未来可能的研究方向以应对这些问题。