  We propose a new neural network architecture for automatic generation of
missing characters in a Chinese font set. We call the neural network
architecture the Variational Grid Setting Network which is based on the
variational autoencoder (VAE) with some tweaks. The neural network model is
able to generate missing characters relatively large in size ($256 \times 256$
pixels). Moreover, we show that one can use very few samples for training data
set, and get a satisfied result.
