[1910.11090] Emotion Generation and Recognition: A StarGAN Approach
Abstract: The main idea of this ISO is to use StarGAN (A type of GAN model) to perform
training and testing on an emotion dataset resulting in a emotion recognition
which can be generated by the valence arousal score of the 7 basic expressions.
We have created an entirely new dataset consisting of 4K videos. This dataset
consists of all the basic 7 types of emotions: Happy, Sad, Angry, Surprised,
Fear, Disgust, Neutral. We have performed face detection and alignment followed
by annotating basic valence arousal values to the frames/images in the dataset
depending on the emotions manually. Then the existing StarGAN model is trained
on our created dataset after which some manual subjects were chosen to test the
efficiency of the trained StarGAN model.