paarthn

I trained it on an AWS instance with grid k520 gpu.

One possible improvement can be training the text embeddings along with the entire model (Instead of using the pretrained embeddings like skip-thought-vectors). It is on my to-do list, I'll try it out.

There is still a long way to go, to be able to do that. The model currently generates 64 X 64 pictures and is trained on a very specific flowers image dataset. Nevertheless, it would be a great idea to experiment with such a dataset (of sketches and descriptions) if available.