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Found 4 papers, 2 papers with code
Latent Disentanglement in Mesh Variational Autoencoders Improves the Diagnosis of Craniofacial Syndromes and Aids Surgical Planning
The use of deep learning to undertake shape analysis of the complexities of the human head holds great promise.
3D Generative Model Latent Disentanglement via Local Eigenprojection
Designing realistic digital humans is extremely complex.
3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces
Learning a disentangled, interpretable, and structured latent representation in 3D generative models of faces and bodies is still an open problem.
Intraoperative Liver Surface Completion with Graph Convolutional VAE
In this work we propose a method based on geometric deep learning to predict the complete surface of the liver, given a partial point cloud of the organ obtained during the surgical laparoscopic procedure.
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