Secondly, the prior common feature c can provide extra information for the sampling network which is supposed to decrease the latent searching space.
similar to the CVAE architecture, the overall objective for our model in the second generation phase is as below: where q φ represents the recognition network and p ϕ is the prior network with φ and ϕ as the trainable parameters; D(•||•) is the regularization term which measures the distance between the two distributions.