Lilly Tech Systems
Intermediate
Generation Methods
Explore the AI techniques used to generate complete 3D characters, from single-photo reconstruction to text-driven generation and parametric body models.
Photo-to-Avatar
The most accessible method: upload a photo and receive a 3D character.
- Ready Player Me: Upload a selfie, get a cross-platform 3D avatar in seconds
- PIFuHD: Research model that reconstructs 3D body shape from a single image
- SMPL-based methods: Estimate body shape parameters from photos using the SMPL body model
Text-to-Avatar
Describe a character and let AI generate the 3D model:
- Leverages text-to-3D generation models (similar to text-to-image but in 3D)
- Growing capability but still lower quality than photo-based methods
- Best for concept generation and non-photorealistic styles
Parametric Body Models
| Model | Developer | Key Feature |
|---|---|---|
| SMPL/SMPL-X | Max Planck Institute | Industry-standard body model with shape and pose parameters |
| GHUM | Generative body model with learned shape space | |
| MetaHuman | Epic Games | Ultra-realistic characters with high-fidelity face and body |
3D Scanning + AI Enhancement
The highest-fidelity approach combines physical scanning with AI:
- Capture with structured light scanner, photogrammetry, or LiDAR (iPhone/iPad)
- AI fills in missing data, fixes topology, and generates clean mesh
- Auto-rigging applies skeletal structure
- Result: photorealistic 3D character ready for animation
Choosing a Method
Decision guide: For gaming/social: Ready Player Me (fast, compatible). For film/visualization: MetaHuman (highest quality). For research/custom: SMPL-based methods (most flexible). For casual: text-to-avatar (easiest).