Lemon Inc. (20240242452). TEXT TO 3D AVATARS simplified abstract
Contents
TEXT TO 3D AVATARS
Organization Name
Inventor(s)
Tiancheng Zhi of Los Angeles CA (US)
Rushikesh Dudhat of Los Angeles CA (US)
Jing Liu of Los Angeles CA (US)
Linjie Luo of Los Angeles CA (US)
TEXT TO 3D AVATARS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240242452 titled 'TEXT TO 3D AVATARS
Simplified Explanation:
The patent application describes a method to create three-dimensional avatars by stylizing a dataset of images based on a user-input text prompt and using it to train a 3D generative adversarial network model.
- Using a stable diffusion model to stylize a dataset of images based on user-input text prompts.
- Training an efficient geometry-aware 3D generative adversarial network model using the stylized dataset of images.
- Generating three-dimensional avatars based on the user's input text prompt.
Potential Applications: This technology can be used in virtual reality applications, gaming, personalized content creation, and digital marketing.
Problems Solved: This technology streamlines the process of creating personalized three-dimensional avatars based on text prompts, making it more efficient and accessible.
Benefits: The technology allows for the creation of unique and customized three-dimensional avatars, enhancing user engagement and personalization in various applications.
Commercial Applications: The technology can be utilized in the entertainment industry for character creation, in marketing for personalized advertising, and in virtual reality for immersive experiences.
Questions about three-dimensional avatars: 1. How does this technology improve the process of creating personalized avatars? 2. What are the potential implications of using 3D avatars in virtual reality applications?
Frequently Updated Research: Stay updated on advancements in 3D avatar creation techniques, improvements in generative adversarial network models, and applications of personalized content creation in various industries.
Original Abstract Submitted
three-dimensional (3d) avatars may be produced by stylizing a dataset of images based on a user-input text prompt input to a stable diffusion model, and using the output stylized dataset of images to train an efficient geometry-aware 3d generative adversarial network (eg3d) model.
