Design representation for performance evaluation of 3D shapes in structure-aware generative design
Xingang Li,
Charles Xie,
Zhenghui Sha
Abstract:Data-driven generative design (DDGD) methods utilize deep neural networks to create novel designs based on existing data. The structure-aware DDGD method can handle complex geometries and automate the assembly of separate components into systems, showing promise in facilitating creative designs. However, determining the appropriate vectorized design representation (VDR) to evaluate 3D shapes generated from the structure-aware DDGD model remains largely unexplored. To that end, we conducted a comparative analys… Show more
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