Abstract:
The paper explores the topic of Facial Action Unit
(FAU) detection in the wild. In particular, we are interested in
answering the following questions: (1) How useful are residual
connections across dense blocks for face analysis? (2) How
useful is the information from a network trained for categorical
Facial Expression Recognition (FER) for the task of FAU detection? The proposed network (ResiDen) exploits dense blocks
along with residual connections and uses auxiliary information
from a FER network. The experiments are performed on the
EmotionNet and DISFA datasets. The experiments show the
usefulness of facial expression information for AU detection.
The proposed network achieves state-of-the-art results on the
two datasets. Analysis of the results for cross dataset protocol
shows the effectiveness of the network.
