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Shape Complexity Estimation Using VAE

  • Markus Rothgänger,
  • Andrew Melnik,
  • Helge Ritter

摘要

In this paper, we compare methods for estimating the complexity of two-dimensional shapes and introduce a method that exploits reconstruction loss of Variational Autoencoders with different sizes of latent vectors. Although complexity of a shape is not a well defined attribute, different aspects of it can be estimated. We demonstrate that our method captures some aspects of shape complexity. Code and training details will be publicly available.