29 citations · 75 across the 6 of their papers we have counts for
7 papers
Building-GAN: Graph-Conditioned Architectural Volumetric Design Generation
Kai-Hung Chang, Chin-Yi Cheng, Jieliang Luo +3
Volumetric design is the first and critical step for professional building design, where architects not only depict the rough 3D geometry of the building but also specify the progr…
Inferring CAD Modeling Sequences Using Zone Graphs
Xianghao Xu, Wenzhe Peng, Chin-Yi Cheng +2
In computer-aided design (CAD), the ability to "reverse engineer" the modeling steps used to create 3D shapes is a long-sought-after goal. This process can be decomposed into two s…
House-GAN++: Generative Adversarial Layout Refinement Networks
Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang +3
This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation. Our architecture is an integration of a graph-constrained relationa…
SketchOpt: Sketch-based Parametric Model Retrieval for Generative Design
Mohammad Keshavarzi, Clayton Hutson, Chin-Yi Cheng +3
Developing fully parametric building models for performance-based generative design tasks often requires proficiency in many advanced 3D modeling and visual programming, limiting i…
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation
Nelson Nauata, Kai-Hung Chang, Chin-Yi Cheng +2
This paper proposes a novel graph-constrained generative adversarial network, whose generator and discriminator are built upon relational architecture. The main idea is to encode t…
Learning to simulate and design for structural engineering
Kai-Hung Chang, Chin-Yi Cheng
The structural design process for buildings is time-consuming and laborious. To automate this process, structural engineers combine optimization methods with simulation tools to fi…
Unsupervised Image to Sequence Translation with Canvas-Drawer Networks
Kevin Frans, Chin-Yi Cheng
Encoding images as a series of high-level constructs, such as brush strokes or discrete shapes, can often be key to both human and machine understanding. In many cases, however, da…