LHM: Large Animatable Human Reconstruction Model
| Property | Value |
|---|---|
| Author | 3DAIGC |
| Available Versions | 500M-HF, 500M, 1B |
| Paper | arXiv:2503.10625 |
| Model Repository | Hugging Face |
What is LHM?
LHM (Large animatable Human reconstruction Model) is a revolutionary feed-forward model designed to create animatable 3D human reconstructions from single images in mere seconds. Developed by researchers at 3DAIGC, it represents a significant advancement in the field of 3D human modeling and animation.
Implementation Details
The model is trained on a large-scale video dataset using image reconstruction loss, enabling robust generalization to diverse real-world scenarios. It comes in three variants: 500M-HF, 500M, and 1B parameter versions, all available through Hugging Face.
- Feed-forward architecture for real-time processing
- Large-scale video dataset training
- Image reconstruction loss optimization
- Multiple model sizes for different use cases
Core Capabilities
- Single-image to 3D human reconstruction
- Fast processing speed (seconds per image)
- Animatable output generation
- Strong generalization to real-world scenarios
Frequently Asked Questions
Q: What makes this model unique?
LHM stands out for its ability to generate animatable 3D human reconstructions from a single image in seconds, combining speed with high-quality results. The model's feed-forward architecture and training on large-scale video data enable robust real-world performance.
Q: What are the recommended use cases?
The model is ideal for applications requiring quick 3D human reconstruction from single images, such as virtual reality, gaming, animation, and digital content creation. Different model sizes (500M and 1B) cater to varying computational resource requirements.
