TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation

@article{Gao2022TetGANAC,
  title={TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation},
  author={William Gao and April Wang and Gal Metzer and Raymond A. Yeh and Rana Hanocka},
  journal={ArXiv},
  year={2022},
  volume={abs/2210.05735}
}
We present TetGAN, a convolutional neural network designed to generate tetrahedral meshes. We represent shapes using an irregular tetrahedral grid which encodes an occupancy and displacement field. Our formulation enables defining tetrahedral convolution, pooling, and upsampling operations to synthesize explicit mesh connectivity with variable topological genus. The proposed neural network layers learn deep features over each tetrahedron and learn to extract patterns within spatial regions across… 

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