Urban modeling facilitates the generation of virtual environments for various scenarios about cities. It requires expertise and consideration, and therefore consumes massive time and computation resources. Nevertheless, related tasks sometimes result in dissatisfaction or even failure. These challenges have received significant attention from researchers in the area of computer graphics. Meanwhile, the burgeoning development of artificial intelligence motivates people to exploit machine learning, and hence improves the conventional solutions. In this paper, we present a review of approaches to urban modeling in computer graphics using machine learning in the literature published between 2010 and 2019. This serves as an overview of the current state of research on urban modeling from a machine learning perspective.

城市建模促进了有关城市各种场景的虚拟环境的生成。它需要专业知识和考虑，因此会消耗大量时间和计算资源。但是，相关任务有时会导致不满意甚至失败。这些挑战已在计算机图形学领域引起了研究人员的极大关注。同时，人工智能的蓬勃发展激励人们利用机器学习，从而改善了传统的解决方案。在本文中，我们对在2010年至2019年之间发表的文献中使用机器学习的计算机图形学中的城市建模方法进行了概述。这从机器学习的角度概述了城市建模的研究现状。