MorphGAN: One-Shot Face Synthesis GAN for Detecting Recognition Bias

Understand

To detect bias in face recognition networks, it can be useful to probe a network under test using samples in which only specific attributes vary in some controlled way.

• However, capturing a sufficiently large dataset with specific control over the attributes of interest is difficult.
• In this work, we describe a simulator that applies specific head pose and facial expression adjustments to images of previously unseen people.
• The simulator first fits a 3D morphable model to a provided image, applies the desired head pose and facial expression controls, then renders the model into an image.