Realistic Facial Attribute Control via Variational Autoencoding
The design and implementation of a generative system based on a variational autoencoder (VAE) for reconstructing and manipulating facial features in images and introduces a selective orthogonalization of latent vectors using the Gram-Schmidt process, informed by correlation matrix analysis.