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README.md
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### Model Description
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Make-A-Shape is a novel 3D generative framework trained on an extensive dataset of over 10 million publicly-available 3D shapes. The voxels(16³) to 3D model is one of the conditional generation models in this framework. It can efficiently generate a wide range of high-quality 3D shapes from
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- **Developed by:** Ka-Hei Hui, Aditya Sanghi, Arianna Rampini, Kamal Rahimi Malekshan, Zhengzhe Liu, Hooman Shayani, Chi-Wing Fu
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- **Model type:** 3D Generative Model
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### Risks and Limitations
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- The quality of the generated 3D output may be impacted by the quality and clarity of the input
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- The model may occasionally generate implausible shapes, especially when the input
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## How to Get Started with the Model
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### Model Description
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Make-A-Shape is a novel 3D generative framework trained on an extensive dataset of over 10 million publicly-available 3D shapes. The voxels(16³) to 3D model is one of the conditional generation models in this framework. It can efficiently generate a wide range of high-quality 3D shapes from 16^3 voxels as inputs. The model uses a wavelet-tree representation and adaptive training strategy to achieve superior performance in terms of geometric detail and structural plausibility.
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- **Developed by:** Ka-Hei Hui, Aditya Sanghi, Arianna Rampini, Kamal Rahimi Malekshan, Zhengzhe Liu, Hooman Shayani, Chi-Wing Fu
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- **Model type:** 3D Generative Model
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### Risks and Limitations
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- The quality of the generated 3D output may be impacted by the quality and clarity of the input.
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- The model may occasionally generate implausible shapes, especially when the input is ambiguous or of low quality. Even theoretically plausible shapes should not be relied upon for real-world structural soundness.
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## How to Get Started with the Model
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