ExprGAN: Facial Expression Editing with Controllable Expression Intensity

Understand

Facial expression editing is a challenging task as it needs a high-level semantic understanding of the input face image.

• In conventional methods, either paired training data is required or the synthetic face resolution is low.
• Moreover, only the categories of facial expression can be changed.
• To address these limitations, we propose an Expression Generative Adversarial Network (ExprGAN) for photo-realistic facial expression editing with controllable expression intensity.