Open MmDawN opened 5 years ago
model_input = multiply([flat_img, label_embedding])
Looks like it's just a way to add label information without increasing input dimension, however I don't know how it's common.
https://stats.stackexchange.com/questions/270546/how-does-keras-embedding-layer-work
Looks like using embedding layer is suggested here: https://github.com/soumith/ganhacks#16-discrete-variables-in-conditional-gans
@mrgloom Thanks for your reply, but is there any formal inference for doing so?
I have the same doubt. In case we have multiple auxiliary inputs, then should we multiply all of their embeddings with the noise or concatenate?
Here, I don't understand why we need to multiply the input image by the label. Don't we need to concat the two part in CGAN? I'll be really appreciate if anyone can help me out!