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Amos Gropp

1 accepted papers

2020

Implicit Geometric Regularization for Learning Shapes

ICML 2020poster

Representing shapes as level-sets of neural networks has been recently proved to be useful for different shape analysis and reconstruction tasks. So far, such representations were computed using either: (i) pre-computed implicit shape representations; or (ii) loss functions explicitly defined over t…