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Found 3 papers, 1 papers with code
WrappingNet: Mesh Autoencoder via Deep Sphere Deformation
There have been recent efforts to learn more meaningful representations via fixed length codewords from mesh data, since a mesh serves as a complete model of underlying 3D shape compared to a point cloud.
GRASP-Net: Geometric Residual Analysis and Synthesis for Point Cloud Compression
Specifically, a point-based network is applied to convert the erratic local details to latent features residing on the coarse point cloud.
Learning Product Graphs Underlying Smooth Graph Signals
However, in cases where the underlying graph is unavailable, it needs to be learned from the data itself for data representation, data processing and inference purposes.
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