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Automatic Measures for Evaluating Generative Design Methods for Architects

2023-03-20 22:34:57
Eric Yeh, Briland Hitaj, Vidyasagar Sadhu, Anirban Roy, Takuma Nakabayashi, Yoshito Tsuji

Abstract

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.

Abstract (translated)

最近的高质量图像对图像方法的爆发引起了对将图像对图像方法应用于艺术和设计任务的兴趣。对建筑师来说,最感兴趣的方法是使用这些方法从概念草图生成设计提案,通常是指手绘的草图,它们可以快速发展并体现设计意图。更具体地说,将草图实例化成为可用于获取客户反馈的视觉通常是一项耗时的任务,并且能够加快迭代时间很重要。虽然生成方法领域的工作令人印象深刻,但用于评估这些系统输出的质量指标与建筑师的实际期望之间存在不匹配。特别是,最近基于图像的作品强调了生成图像的真实感。虽然重要,但这是建筑师寻找的其他标准之一。在本研究中,我们描述了建筑师从概念草图生成设计提案的期望,并从文献中识别相应的自动化指标。然后我们评估了几种可能解决这些标准的图像对图像生成方法,并检查它们在这些指标上的性能。从这些结果中,我们识别了手绘概念草图的一些挑战,并描述了可能用于解决这些问题的未来的研究方向。

URL

https://arxiv.org/abs/2303.11483

PDF

https://arxiv.org/pdf/2303.11483.pdf


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