This is a study of hierarchical VAE to generate high-definition images. Instead of having the variance and average calculated directly at each stage, they design the distribution taking into account the relative average of the previous layer. In addition, there are various innovations such as swish activation, cells with SE modules, spectral norm, and depth-wise conv for wide receptive field with low calculation cost.
TL;DR
This is a study of hierarchical VAE to generate high-definition images. Instead of having the variance and average calculated directly at each stage, they design the distribution taking into account the relative average of the previous layer. In addition, there are various innovations such as swish activation, cells with SE modules, spectral norm, and depth-wise conv for wide receptive field with low calculation cost.
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https://arxiv.org/abs/2007.03898
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