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We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-and-extrude modeling operations.
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Formalising design exploration as co-evolution
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Partial entity structure: A compact non-manifold boundary representation based on partial topological entities
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A full parametric model for turbomachinery blade design and optimisation
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Computer-based design synthesis research: an overview
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How do humans sketch objects?
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Parametric cad modeling: An analysis of strategies for design reusability
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2017
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beta-vae: Learning basic visual concepts with a constrained variational framework
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Programming language tools and techniques for 3d printing
Nandi, C., Caspi, A., Grossman, D., and Tatlock, Z · 2017
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Neural discrete representation learning
van den Oord, A., Vinyals, O., and Kavukcuoglu, K · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., and Polosukhin, I · 2017
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Learning representations and generative models for 3d point clouds
Achlioptas, P., Diamanti, O., Mitliagkas, I., and Guibas, L · 2018
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Inversecsg: Automatic conversion of 3d models to csg trees
Du, T., Inala, J. P., Pu, Y., Spielberg, A., Schulz, A., Rus, D., Solar-Lezama, A., and Matusik, W · 2018
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Functional programming for compiling and decompiling computer-aided design
Nandi, C., Wilcox, J. R., Panchekha, P., Blau, T., Grossman, D., and Tatlock, Z · 2018
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Csgnet: Neural shape parser for constructive solid geometry
Sharma, G., Goyal, R., Liu, D., Kalogerakis, E., and Maji, S · 2018
Ucsg-net–unsupervised discovering of constructive solid geometry tree
Kania, K., Zięba, M., and Kajdanowicz, T · 2020
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Polygen: An autoregressive generative model of 3d meshes
Nash, C., Ganin, Y., Eslami, S. M. A., and Battaglia, P. W · 2020
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SketchGraphs: A large-scale dataset for modeling relational geometry in computer-aided design
Seff, A., Ovadia, Y., Zhou, W., and Adams, R. P · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., and Houlsby, N · 2021
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Taming transformers for high-resolution image synthesis
Esser, P., Rombach, R., and Ommer, B · 2021
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Computer-aided design as language
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Pytorch: An imperative style, high-performance deep learning library
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Generating diverse high-fidelity images with vq-vae-2
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Learning to infer and execute 3d shape programs
Tian, Y., Luo, A., Sun, X., Ellis, K., Freeman, W. T., Tenenbaum, J. B., and Wu, J · 2019
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Bsp-net: Generating compact meshes via binary space partitioning
Chen, Z., Tagliasacchi, A., and Zhang, H · 2020
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BézierSketch: A Generative Model for Scalable Vector Sketches
Das, A., Yang, Y., Hospedales, T., Xiang, T., and Song, Y.-Z · 2020
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Ganin, Y., Bartunov, S., Li, Y., Keller, E., and Saliceti, S · 2021
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Sketchgen: Generating constrained cad sketches
Para, W. R., Bhat, S. F., Guerrero, P., Kelly, T., Mitra, N., Guibas, L., and Wonka, P · 2021
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Engineering sketch generation for computer-aided design
Willis, K. D. D., Jayaraman, P. K., Lambourne, J. G., Chu, H., and Pu, Y · 2021
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Deepcad: A deep generative network for computer-aided design models
Wu, R., Xiao, C., and Zheng, C · 2021
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Inferring cad modeling sequences using zone graphs
Xu, X., Peng, W., Cheng, C.-Y., Willis, K. D., and Ritchie, D · 2021
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Vitruvion: A generative model of parametric cad sketches
Seff, A., Zhou, W., Richardson, N., and Adams, R. P · 2022
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Capri-net: Learning compact cad shapes with adaptive primitive assembly
Yu, F., Chen, Z., Li, M., Sanghi, A., Shayani, H., Mahdavi-Amiri, A., and Zhang, H · 2022
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