MobileStyleGAN: A Lightweight Convolutional Neural Network for High-Fidelity Image Synthesis

Understand

In recent years, the use of Generative Adversarial Networks (GANs) has become very popular in generative image modeling.

• While style-based GAN architectures yield state-of-the-art results in high-fidelity image synthesis, computationally, they are highly complex.
• In our work, we focus on the performance optimization of style-based generative models.
• We analyze the most computationally hard parts of StyleGAN2, and propose changes in the generator network to make it possible to deploy style-based generative networks in the edge devices.