A part-based neural deformation model disentangles motion and shape spaces in a diffusion-based 4D generator, outperforming prior work on unconditional and conditional 4D shape tasks.
arXiv preprint arXiv:2002.00349 (2020)
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Learning Neural Deformation Representation for 4D Dynamic Shape Generation
A part-based neural deformation model disentangles motion and shape spaces in a diffusion-based 4D generator, outperforming prior work on unconditional and conditional 4D shape tasks.