The open rapid access of AI generative design tools (Text to 3D) to morphological expression of the cortical-trabecular hierarchical
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https://doi.org/10.18682/cdc.vi262.12241
Résumé
Artificial Intelligence generative design tools are developing rapidly and revolutionizing their application in the design to fabrication processes.
Références
Abdallah, Y.K. and Estévez, A.T. (2023). Biomaterials Research-Driven Design Visualized by AI Text-Prompt-Generated Images. Designs, 7(2), 48. https://doi.org/10.3390/designs7020048.
Estévez, A.T. and Abdallah, Y.K. (2024). Biomimetic Approach for Enhanced Mechanical Properties and Stability of Self-Mineralized Calcium Phosphate Dibasic–Sodium Alginate– Gelatine Hydrogel as Bone Replacement and Structural Building Material. Processes, 12, 944. https://doi.org/10.3390/pr12050944
Bhat, S.F., Birkl, R., Wofk, D., Wonka, P. and Müller, M. (2023). ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth. [online] arXiv.org. https://doi.org/10.48550/arXiv.2302.12288.
Chun, E., Lin, C.Z., Matthew, Nagano, K., Pan, B., Shalini de Mello, Gallo, O., Leonidas Guibas, Tremblay, J., Khamis, S., Karras, T. and Wetzstein, G. (2022). Efficient Geometry-aware 3D Generative Adversarial Networks. https://doi.org/10.1109/cvpr52688.2022.01565.
Gao, J., Shen, T., Wang, Z., Chen, W., Yin, K., Li, D., Litany, O., Gojcic, Z., and Fidler, S. (2022). Get3d: A generative model of high quality 3d textured shapes learned from images. Advances in Neural Information Processing Systems, 1, 2, 3.
Estévez, A.T. and Abdallah, Y.K. (2024). Biomimetic Approach for Enhanced Mechanical Properties and Stability of Self-Mineralized Calcium Phosphate Dibasic–Sodium Alginate– Gelatine Hydrogel as Bone Replacement and Structural Building Material. Processes, 12, 944. https://doi.org/10.3390/pr12050944
Bhat, S.F., Birkl, R., Wofk, D., Wonka, P. and Müller, M. (2023). ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth. [online] arXiv.org. https://doi.org/10.48550/arXiv.2302.12288.
Chun, E., Lin, C.Z., Matthew, Nagano, K., Pan, B., Shalini de Mello, Gallo, O., Leonidas Guibas, Tremblay, J., Khamis, S., Karras, T. and Wetzstein, G. (2022). Efficient Geometry-aware 3D Generative Adversarial Networks. https://doi.org/10.1109/cvpr52688.2022.01565.
Gao, J., Shen, T., Wang, Z., Chen, W., Yin, K., Li, D., Litany, O., Gojcic, Z., and Fidler, S. (2022). Get3d: A generative model of high quality 3d textured shapes learned from images. Advances in Neural Information Processing Systems, 1, 2, 3.
Publiée
2025-04-07
Comment citer
Abdallah, Y. K., & Estévez, A. T. (2025). The open rapid access of AI generative design tools (Text to 3D) to morphological expression of the cortical-trabecular hierarchical. Cuadernos Del Centro De Estudios De Diseño Y Comunicación, (262). https://doi.org/10.18682/cdc.vi262.12241
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Artículos
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