All's well that FID's well? Result quality and metric scores in GAN models for lip-sychronization tasks

Carina Geldhauser, Johan Liljegren, Pontus Nordqvist

Abstract: We test the performance of GAN models for lip-synchronization. For this, we reimplement LipGAN in Pytorch, train it on the dataset GRID and compare it to our own variation, L1WGAN-GP, adapted to the LipGAN architecture and also trained on GRID.