Corpus ID: 6530726

Challenges in Disentangling Independent Factors of Variation

@article{Szab2018ChallengesID,
  title={Challenges in Disentangling Independent Factors of Variation},
  author={A. Szab{\'o} and Qiyang Hu and Tiziano Portenier and Matthias Zwicker and P. Favaro},
  journal={ArXiv},
  year={2018},
  volume={abs/1711.02245}
}

A. Szabó, Qiyang Hu, +2 authors P. Favaro

Published 2018

Computer Science

ArXiv

We study the problem of building models that disentangle independent factors of variation. Such models could be used to encode features that can efficiently be used for classification and to transfer attributes between different images in image synthesis. As data we use a weakly labeled training set. Our weak labels indicate what single factor has changed between two data samples, although the relative value of the change is unknown. This labeling is of particular interest as it may be readily… CONTINUE READING

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