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This paper presents a novel generative model for Computer Aided Design (CAD) that 1) represents high-level design concepts of a CAD model as a three-level hierarchical tree of neural codes, from global part arrangement down to local curve geometry; and 2) controls the generation or completion of CAD models by specifying the target design using a code tree.
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Guo, H., Liu, S., Pan, H., Liu, Y., Tong, X., and Guo, B · 2022
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He, K., Chen, X., Xie, S., Li, Y., Dollár, P., and Girshick, R · 2022
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Jayaraman, P. K., Lambourne, J. G., Desai, N., Willis, K. D. D., Sanghi, A., and Morris, N. J. W · 2022
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Lambourne, J. G., Willis, K. D., Jayaraman, P. K., Zhang, L., Sanghi, A., and Malekshan, K. R · 2022
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Li, C., Pan, H., Bousseau, A., and Mitra, N. J · 2022
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Li, C., Pan, H., Bousseau, A., and Mitra, N. J · 2020
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Seff, A., Ovadia, Y., Zhou, W., and Adams, R. P · 2020
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Sharma, G., Liu, D., Maji, S., Kalogerakis, E., Chaudhuri, S., and Měch, R · 2020
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Ganin, Y., Bartunov, S., Li, Y., Keller, E., and Saliceti, S · 2021
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The failed promise of parametric cad, 2013
Yares, E · 2022
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