Image-to-3D
Safetensors
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@@ -39,7 +39,7 @@ Please note: For individuals or organizations generating annual revenue of US $1
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  * **Developed by**: [Stability AI](https://stability.ai/)
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  * **Model type**: Transformer image-to-3D model
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  * **Model details**: This model is trained to create a 3D model from a single image in under one second. The asset is UV-unwrapped and textured. We also perform a delighting step, enabling easier asset usage in downstream applications such as game engines or rendering work. The model also predicts per-object material parameters (roughness, metallic), enhancing reflective behaviors during rendering. The model expects an input size of 512x512 pixels. We achieve improved backside modelling using a fast point diffusion model, which acts as a conditioning.
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- Please check our [tech report]() and [video summary](https://youtu.be/mlO3Nc3Nsng) for details.
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  ### License
@@ -50,10 +50,10 @@ Please check our [tech report]() and [video summary](https://youtu.be/mlO3Nc3Nsn
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  ### Model Sources
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  * **Repository**: [https://github.com/Stability-AI/stable-point-aware-3d](https://github.com/Stability-AI/stable-point-aware-3d)
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- * **Tech report**: soon
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  * **Video summary**: [https://youtu.be/mlO3Nc3Nsng](https://youtu.be/mlO3Nc3Nsng)
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  * **Project page**: [https://spar3d.github.io](https://spar3d.github.io)
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- * **arXiv page**: soon
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  ### Training Dataset
 
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  * **Developed by**: [Stability AI](https://stability.ai/)
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  * **Model type**: Transformer image-to-3D model
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  * **Model details**: This model is trained to create a 3D model from a single image in under one second. The asset is UV-unwrapped and textured. We also perform a delighting step, enabling easier asset usage in downstream applications such as game engines or rendering work. The model also predicts per-object material parameters (roughness, metallic), enhancing reflective behaviors during rendering. The model expects an input size of 512x512 pixels. We achieve improved backside modelling using a fast point diffusion model, which acts as a conditioning.
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+ Please check our [tech report](arxiv.org/abs/2501.04689) and [video summary](https://youtu.be/mlO3Nc3Nsng) for details.
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  ### License
 
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  ### Model Sources
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  * **Repository**: [https://github.com/Stability-AI/stable-point-aware-3d](https://github.com/Stability-AI/stable-point-aware-3d)
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+ * **Tech report**: [https://arxiv.org/pdf/2501.04689](https://arxiv.org/pdf/2501.04689)
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  * **Video summary**: [https://youtu.be/mlO3Nc3Nsng](https://youtu.be/mlO3Nc3Nsng)
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  * **Project page**: [https://spar3d.github.io](https://spar3d.github.io)
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+ * **arXiv page**: [https://arxiv.org/abs/2501.04689](https://arxiv.org/abs/2501.04689)
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  ### Training Dataset