---
title: TripoSR
canonical_url: "https://www.modelscope.cn/models/AI-ModelScope/TripoSR"
md_url: "https://www.modelscope.cn/models/AI-ModelScope/TripoSR.md"
repository: AI-ModelScope/TripoSR
last_updated: 2024-03-09
license: mit
pipeline_tag: image-to-3D
tasks:
  - image-to-3D
library_name:
  - pytorch
frameworks:
  - pytorch
downloads: 289
stars: 0
tags:
  - 3d
---

# TripoSR

> TripoSR - AI-ModelScope 在 ModelScope 开源的模型。TripoSR TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI.

AI-ModelScope/TripoSR 是 ModelScope 魔搭社区上的image-to-3D模型，采用 mit 许可。

- **Repository**: AI-ModelScope/TripoSR
- **License**: mit
- **Tasks**: image-to-3D
- **Tags**: 3d
- **Downloads**: 289
- **Stars**: 0
- **Last updated**: 2024-03-09

Source: https://www.modelscope.cn/models/AI-ModelScope/TripoSR

---

# TripoSR
![](figures/input800.mp4)
TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI.

## Model Details

### Model Description

We closely follow [LRM](https://arxiv.org/abs/2311.04400) network architecture for the model design, where TripoSR incorporates a series of technical advancements over the LRM model in terms of both data curation as well as model and training improvements. For more technical details and evaluations, please refer to [our tech report](https://arxiv.org/abs/2403.02151).

* **Developed by**: [Stability AI](https://stability.ai/), [Tripo AI](https://tripo3d.ai/)
* **Model type**: Feed-forward 3D reconstruction from a single image
* **License**: MIT
* **Hardware**: We train `TripoSR` for 5 days on 22 GPU nodes each with 8 A100 40GB GPUs

### Model Sources

* **Repository**: https://github.com/VAST-AI-Research/TripoSR
* **Tech report**: https://arxiv.org/abs/2403.02151
* **Demo**: https://huggingface.co/spaces/stabilityai/TripoSR

### Training Dataset

We use renders from the [Objaverse](https://objaverse.allenai.org/objaverse-1.0) dataset, utilizing our enhanced rendering method that more closely replicate the distribution of images found in the real world, significantly improving our model’s ability to generalize. We selected a carefully curated subset of the Objaverse dataset for the training data, which is available under the CC-BY license. 


## Usage

* For usage instructions, please refer to our [TripoSR GitHub repository](https://github.com/VAST-AI-Research/TripoSR)

* You can also try it in [our gradio demo](https://huggingface.co/spaces/stabilityai/TripoSR)


### Misuse, Malicious Use, and Out-of-Scope Use

The model should not be used to intentionally create or disseminate 3D models that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.