Nvidia corporation (20240290054). TEXT-DRIVEN 3D OBJECT STYLIZATION USING NEURAL NETWORKS simplified abstract
Contents
TEXT-DRIVEN 3D OBJECT STYLIZATION USING NEURAL NETWORKS
Organization Name
Inventor(s)
Masha Shugrina of Toronto (CA)
Sameh Khamis of Alameda CA (US)
TEXT-DRIVEN 3D OBJECT STYLIZATION USING NEURAL NETWORKS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240290054 titled 'TEXT-DRIVEN 3D OBJECT STYLIZATION USING NEURAL NETWORKS
The abstract describes a method for generating three-dimensional (3D) object models using style transfer networks combined with a generative network, based on textual input parameters.
- Style transfer networks are combined with a generative network to create 3D objects from textual input.
- Input includes a 3D mesh and texture, along with parameters for object generation in the textual input.
- Features of the input object are identified and adjusted according to the textual input to generate a modified 3D object.
- The modified object includes a new texture and geometric adjustments.
Potential Applications: - Rapid prototyping in design industries - Customization of 3D models in gaming and entertainment - Automated generation of 3D objects for virtual reality applications
Problems Solved: - Simplifying the process of creating 3D objects for users with limited skills - Reducing the resource intensity of 3D object modeling
Benefits: - Faster and more efficient generation of 3D objects - Increased flexibility and customization options for users - Improved accessibility to 3D modeling technology
Commercial Applications: Title: Automated 3D Object Generation Technology for Design and Entertainment Industries This technology can be used in design, gaming, entertainment, and virtual reality industries to streamline the process of creating and customizing 3D objects, leading to cost savings and increased productivity.
Questions about 3D Object Generation Technology: 1. How does this technology compare to traditional 3D modeling methods? This technology offers a more automated and user-friendly approach to generating 3D objects compared to traditional modeling methods, making it accessible to a wider range of users.
2. What are the potential limitations of using style transfer networks in 3D object generation? While style transfer networks can enhance the visual appearance of 3D objects, they may introduce artifacts or distortions in the final output, requiring careful tuning and optimization.
Original Abstract Submitted
generation of three-dimensional (3d) object models may be challenging for users without a sufficient skill set for content creation and may also be resource intensive. one or more style transfer networks may be combined with a generative network to generate objects based on parameters associated with a textual input. an input including a 3d mesh and texture may be provided to a trained system along with a textual input that includes parameters for object generation. features of the input object may be identified and then tuned in accordance with the textual input to generate a modified 3d object that includes a new texture along with one or more geometric adjustments.
