FAME: 3D Shape Generation via Functionality-Aware Model Evolution
Type
ArticleAuthors
Guan, YanranLiu, Han

Liu, Kun
Yin, Kangxue
Hu, Ruizhen
van Kaick, Oliver
Zhang, Yan
Yumer, Ersin
Carr, Nathan
Mech, Radomir
Zhang, Hao
KAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Date
2020-10-12Online Publication Date
2020-10-12Print Publication Date
2020Submitted Date
2019-05-22Permanent link to this record
http://hdl.handle.net/10754/665541
Metadata
Show full item recordAbstract
We introduce a modeling tool which can evolve a set of 3D objects in a functionality-aware manner. Our goal is for the evolution to generate large and diverse sets of plausible 3D objects for data augmentation, constrained modeling, as well as open-ended exploration to possibly inspire new designs. Starting with an initial population of 3D objects belonging to one or more functional categories, we evolve the shapes through part re-combination to produce generations of hybrids or crossbreeds between parents from the heterogeneous shape collection. Evolutionary selection of offsprings is guided both by a functional plausibility score derived from functionality analysis of shapes in the initial population and user preference, as in a design gallery. Since cross-category hybridization may result in offsprings not belonging to any of the known functional categories, we develop a means for functionality partial matching to evaluate functional plausibility on partial shapes. We show a variety of plausible hybrid shapes generated by our functionality-aware model evolution, which can complement existing datasets as training data and boost the performance of contemporary data-driven segmentation schemes, especially in challenging cases.Citation
Guan, Y., Liu, H., Liu, K., Yin, K., Hu, R., van Kaick, O., … Zhang, H. (2021). FAME: 3D Shape Generation via Functionality-Aware Model Evolution. IEEE Transactions on Visualization and Computer Graphics, 1–1. doi:10.1109/tvcg.2020.3029759arXiv
2005.04464Additional Links
https://ieeexplore.ieee.org/document/9220814/https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9220814
http://arxiv.org/pdf/2005.04464
ae974a485f413a2113503eed53cd6c53
10.1109/TVCG.2020.3029759