Natural-Language 3D Head Generation with NeRF and CLIP
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Solution Overview
Problem
Creating characters and their accoutrements for computer simulations such as computer games is time-consuming and requires professional expertise.
Innovation Solution
A system that uses a neural radiance field (NeRF) generated from images and modified using a Contrastive Language-Image Pre-training (CLIP) model to generate a 3D virtual human head from text input, which is then converted to a polygonal mesh for presentation in a computer simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to create characters and accoutrements for computer simulations, then professional expertise and manual effort are required, but the process becomes time-consuming and complex
Solution Approach 1:
The patent replaces manual mechanical character creation processes with an automated neural radiance field system. The system uses neural networks to generate 3D character models from text descriptions, substituting the mechanical workflow of manual modeling, texturing, and animation with an automated AI-driven process that requires no professional expertise.
Solution Approach 2:
The system transforms character creation by changing the input parameters from complex 3D modeling data to simple text descriptions. The neural radiance field model learns to map text parameters directly to 3D character properties, fundamentally altering the parameter space required for character generation and enabling rapid creation without specialized knowledge.
2Manufacturing precision
If detailed 3D character models are created manually, then high quality and coherence are achieved, but the creation time increases significantly
Solution Approach 1:
The system performs preliminary training of the neural radiance field model on a dataset of 3D character models and their corresponding text descriptions. This preliminary action enables the model to learn the complex mappings between text and 3D properties in advance, so that during actual character creation, high-quality coherent models can be generated rapidly from text without manual intervention.
3Ease of operation
If professional tools and workflows are used for character creation, then control and precision are maintained, but the ease of operation decreases
Solution Approach 1:
The system creates simplified copies or representations of complex 3D character models through text descriptions. Instead of requiring users to manipulate complex 3D tools, the system copies the essential character properties from text input and generates the full 3D model automatically, making the process accessible to non-experts while maintaining precision through the trained neural model.
Data Source
AI summary
Two dimensional images are converted to a 3D neural radiance field (NeRF), which is modified based on text input to resemble the type of character demanded by the text. An open-source “CLIP” model scores how well an image matches a line of text to produce a final 3D NeRF, which may be converted to a polygonal mesh and imported into a computer simulation such as a computer game.