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Attila Szabo

2 accepted papers

2018

Challenges in Disentangling Independent Factors of Variation

Attila Szabo, Qiyang Hu, Tiziano Portenier, Matthias Zwicker, Paolo Favaro
ICLR 2018workshop

We study the problem of building models that disentangle independent factors of variation. Such models 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, where labels in…

Cited by 63Source ↗Scholar ↗
2018

Understanding Degeneracies and Ambiguities in Attribute Transfer

Attila Szabo, Qiyang Hu, Tiziano Portenier, Matthias Zwicker, Paolo Favaro
ECCV 2018poster

We study the problem of building models that can transfer selected attributes from one image to another without affecting the other attributes. Towards this goal, we develop analysis and a training methodology for autoencoding models, whose encoded features aim to disentangle attributes. These featu…

Cited by 14Source ↗PDF ↗Scholar ↗