Learning Stylized Character Expressions from Humans

We present DeepExpr, a novel expression transfer system from humans to multiple stylized characters via deep learning. We developed : 1) a data-driven perceptual model of facial expressions, 2) a novel stylized character data set with cardinal expression annotations : FERG (Facial Expression Research Group) - DB (added two new characters), and 3) . We evaluated our method on a set of retrieval tasks on our collected stylized character dataset of expressions. We have also shown that the ranking order predicted by the proposed features is highly correlated with the ranking order provided by a facial expression expert and Mechanical Turk (MT) experiments.
Comment: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Women in Computer Vision (WiCV) Workshop Honolulu, Hawaii, USA, July 21st - July 26th, 2017