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datasets: |
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- allenai/objaverse |
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tags: |
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- 3d |
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extra_gated_fields: |
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Name: text |
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Email: text |
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Country: text |
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Organization or Affiliation: text |
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I ALLOW Stability AI to email me about new model releases: checkbox |
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license: mit |
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pipeline_tag: image-to-3d |
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--- |
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# TripoSR |
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TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI. |
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## Model Details |
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### Model Description |
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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). |
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* **Developed by**: [Stability AI](https://stability.ai/), [Tripo AI](https://tripo3d.ai/) |
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* **Model type**: Feed-forward 3D reconstruction from a single image |
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* **License**: MIT |
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* **Hardware**: We train `TripoSR` for 5 days on 22 GPU nodes each with 8 A100 40GB GPUs |
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### Model Sources |
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* **Repository**: https://github.com/VAST-AI-Research/TripoSR |
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* **Tech report**: https://arxiv.org/abs/2403.02151 |
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* **Demo**: https://huggingface.co/spaces/stabilityai/TripoSR |
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### Training Dataset |
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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. |
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## Usage |
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* For usage instructions, please refer to our [TripoSR GitHub repository](https://github.com/VAST-AI-Research/TripoSR) |
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* You can also try it in [our gradio demo](https://huggingface.co/spaces/stabilityai/TripoSR) |
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### Misuse, Malicious Use, and Out-of-Scope Use |
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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. |
