Enhancing variational generation through self-decomposition

In this article we introduce the notion of Split Variational Autoencoder (SVAE), whose output $\hat{x}$ is obtained as a weighted sum $σ\odot \hat{x_1} + (1-σ) \odot \hat{x_2}$ of two generated images $\hat{x_1},\hat{x_2}$, and $σ$ is a {\em learned} compositional map. The composing images $\hat{x_1},\hat{x_2}$, as well as the $σ$-map are automatically synthesized by the model. The network is t…