The is the implementation of the paper: Latent Space is Feature Space: Regularization Term for GANs Training on Limited Dataset, and the original lab environment.
The useful implementation are in the src folder, where I have implemented DCGAN and DCGAN with LFM. The lab.py is to loop over configurations for generating results of comparison tests.
If you have any question about the LFM or the result, feel free to contact me. LFM did not show great result on CelebA when the dataset size went over 20k images, while might improve the performance with small size datasets from 500 to 2k images.