ALAE

Why we included this project

ALAE tackles a question most GAN practitioners run into: how to edit a real photo when your generator can only sample from random noise. It pairs an encoder with an adversarial generator, so a real face can be mapped into latent space and then reconstructed or manipulated at a quality comparable to StyleGAN. The official PyTorch implementation trains on FFHQ and CelebA-HQ, produces 1024x1024 face outputs, and ships pretrained models plus qualitative results so you can judge the behavior before committing to a full training run. For anyone comparing autoencoders against plain GANs, the StyleGAN-based variant is the instructive part: it shows how to bolt an encoder onto an already capable generator.