There are several approaches to generating 3d assets from text using ML models, however, the field is still in its infancy:
 * One approach is to train a model on a specific object class and condition on a segmentation or edge map. This approach is implemented by the "Pix2pix3D" model by Deng, et al. The model yields a NERF which can be converted to a mesh with tools such as those provided by Instant-NGP.
 * Another approach is to optimize a NERF using a 2d diffusion model as a prior as is taken in DreamFusion by Poole, et al. The same approach as above could be taken to convert this NERF into a traditional 3d model if desired.
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