The Nuts and Bolts of Adopting Transformer in GANs

Understand

Transformer becomes prevalent in computer vision, especially for high-level vision tasks.

• However, adopting Transformer in the generative adversarial network (GAN) framework is still an open yet challenging problem.
• In this paper, we conduct a comprehensive empirical study to investigate the properties of Transformer in GAN for high-fidelity image synthesis.
• Our analysis highlights and reaffirms the importance of feature locality in image generation, although the merits of the locality are well known in the classification task.