| --- |
| license: mit |
| pipeline_tag: image-to-3d |
| tags: |
| - triposg |
| - 3d-generation |
| - rectified-flow |
| --- |
| # TripoSG-scribble - Fast 3D Shape Prototyping with Scribble and Prompt |
|
|
| TripoSG-scribble converts a scribble image and a text prompt to a 3D shape. TripoSG-scribble is a variant of TripoSG. 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 |
|
|
| For inference efficiency, TripoSG-scribble is different from TripoSG in: |
| - TripoSG-scribble is a CFG-distilled model and should be used with CFG=0 |
| - TripoSG-scribble is trained with 512 latent tokens |
|
|
| ## Intended Uses |
|
|
| This model is designed for: |
| - Converting scribble image and text prompt 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-scribble 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-scribble) |
