|
|
--- |
|
|
license: mit |
|
|
pipeline_tag: image-to-3d |
|
|
tags: |
|
|
- triposg |
|
|
- 3d-generation |
|
|
- rectified-flow |
|
|
--- |
|
|
# TripoSG - High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models |
|
|
|
|
|
TripoSG is a state-of-the-art image-to-3D generation foundation model that leverages large-scale rectified flow transformers to produce high-fidelity 3D shapes from single images. |
|
|
|
|
|
## Model Description |
|
|
|
|
|
### Model Architecture |
|
|
|
|
|
TripoSG utilizes a novel architecture combining: |
|
|
- Rectified Flow (RF) based Transformer for stable, linear trajectory modeling |
|
|
- Advanced VAE with SDF-based representation and hybrid geometric supervision |
|
|
- Cross-attention mechanism for image feature condition |
|
|
- 1.5B parameters operating on 2048 latent tokens |
|
|
|
|
|
## Intended Uses |
|
|
|
|
|
This model is designed for: |
|
|
- Converting single images to high-quality 3D meshes |
|
|
- Creative and design applications |
|
|
- Gaming and VFX asset creation |
|
|
- Prototyping and visualization |
|
|
|
|
|
## Requirements |
|
|
|
|
|
- CUDA-capable GPU (>8GB VRAM) |
|
|
|
|
|
## Usage |
|
|
|
|
|
For detailed usage instructions, please visit our [GitHub repository](https://github.com/VAST-AI-Research/TripoSG). |
|
|
|
|
|
## About |
|
|
|
|
|
TripoSG is developed by [Tripo](https://www.tripo3d.ai), [VAST AI Research](https://github.com/orgs/VAST-AI-Research), pushing the boundaries of 3D Generative AI. |
|
|
For more information: |
|
|
- [GitHub Repository](https://github.com/VAST-AI-Research/TripoSG) |
|
|
- [Paper](https://arxiv.org/abs/2502.06608) |
|
|
- [Gradio Demo](https://huggingface.co/spaces/VAST-AI/TripoSG) |
