핵심 개념
Generative AI tools must consider physical functionality and fabrication constraints to enable the creation of visually appealing yet practically viable 3D models.
초록
This paper highlights the limitations of current 3D generative AI tools in translating digital creations into the physical world and proposes new approaches to address this challenge.
The key ideas discussed are:
Preserving Functionality:
- Identifying functional regions in 3D models and preserving them during aesthetic manipulations
- Developing "smart" manipulation techniques that allow safe stylization while maintaining intended functionality
- Considering the interdependence between functional and aesthetic segments of a model
Encoding Functionality:
- Incorporating material properties into the generative process
- Integrating simulation and testing within the AI pipeline to ensure functional viability
- Accounting for geometrical complexities and enabling user-centric customization
- Implementing feedback loops for continuous improvement of generated models
By addressing these aspects, the paper advocates for the development of generative AI tools that can create 3D models not just for digital aesthetics, but also for real-world fabrication and functionality. This would bridge the gap between digital creativity and physical applicability, extending the potential of generative AI into the tangible domain.