Eye in-painting using WGAN-GP for face images with mosaic
Cheng-Hsuan Wu, Hsien-Tsung Chang, Ammar Amjad · 2020
In order to protect personal privacy, news reports often use the mosaics upon the face of the protagonist in the photo. However, readers will feel uncomfortable and awkward to this kind of photos. In this research, we detect the eye mosaic and try to use eye complementing which is not the same with original picture but matches the nearby texture. It can arouse readers' interest in reading. Traditional in-painting research is not suitable for filling special or large objects, such as eyes or boxes on the ground. They only can fill a small area of missing parts or a single background refer to nearby textures, such as landscape photos. We use WGAN-GP that can refer to nearby textures to generate special objects for in-painting eyes. We also divide the training set into male and female according to gender to avoid eye makeup appearing in all pictures. The experiment result shows our method get higher score in blind testing.