TL-GAN is an extension of NVIDIA’s pg-GAN which took the machine learning community by storm with its impressive ability to generate hyperreaslitic images of humans.
TL-GAN takes the pc-GAN one step further by deriving a feature vector formed by the latent space that enables us to peer into the “black box”. In doing so, we can adjust the weights of features to generate customizable faces. Use cases include stock photo generation, data augmentation, and smart editing that are all functions of the ability to product realistic, unique images of faces.
The image above showcases the matrix of feature combinations. These features range from more general such as gender and age to more specific features such as bang length. Using this we can generate hyper realistic images that match our intended use case.
Link to slides:
https://docs.google.com/presentation/d/1sq-xTaZPPEkkh1i-434o1nyJQbRxpOPeWMkq3c_AaQc/edit?usp=sharing