AdversarialNAS: Adversarial Neural Architecture Search for GANs

Understand

Neural Architecture Search (NAS) that aims to automate the procedure of architecture design has achieved promising results in many computer vision fields.

• In this paper, we propose an AdversarialNAS method specially tailored for Generative Adversarial Networks (GANs) to search for a superior generative model on the task of unconditional image generation.
• The AdversarialNAS is the first method that can search the architectures of generator and discriminator simultaneously in a differentiable manner.
• During searching, the designed adversarial search algorithm does not need to comput any extra metric to evaluate the performance of the searched architecture, and the search paradigm considers the relevance between the two network architectures and improves their mutual balance.