HyperStyle learns to modulate StyleGAN’s weights via a hypernetwork to faithfully reconstruct real images while maintaining editability in the latent space. The approach reduces what would be billions of parameters to a manageable size through careful network design. It achieves reconstruction quality comparable to optimization-based techniques while providing near real-time inference through encoder-based inversion.