Training the GIRAFFE model
So far in this chapter, we have understood how a trained GIRAFFE model works. We have understood the different components that make up the generator part of the model.
But to train the model, there is another part that we have not looked at so far, namely, the discriminator. Like in any other GAN model, this discriminator part of the model is not used during image synthesis, but it is a vital component for training the model. In this chapter, we will investigate it in more detail and gain an understanding of the loss function used. We will train a new model from scratch using the training module provided by the authors of GIRAFFE.
The generator takes as input the various latent code corresponding to object rotation, background rotation, camera elevation, horizontal and depth translation, and object size. This is used to first generate a feature field and then map it to RGB pixels using a neural rendering module. This is the generator. The discriminator...
