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cs.CV2019
DispVoxNets: Non-Rigid Point Set Alignment with Supervised Learning Proxies
Soshi Shimada, Vladislav Golyanik, Edgar Tretschk +2
We introduce a supervised-learning framework for non-rigid point set alignment of a new kind - Displacements on Voxels Networks (DispVoxNets) - which abstracts away from the point…
cs.CV2019
DEMEA: Deep Mesh Autoencoders for Non-Rigidly Deforming Objects
Edgar Tretschk, Ayush Tewari, Michael Zollhöfer +2
Mesh autoencoders are commonly used for dimensionality reduction, sampling and mesh modeling. We propose a general-purpose DEep MEsh Autoencoder (DEMEA) which adds a novel embedded…