Reviews: Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition

The paper explores a method for exploiting multi-view training with label co-regularization for facial action unit recognition. A method for exploiting unlabeled data for the task of action unit recognition which is consistently data poor, so such a method could contribute a lot to the field. One major risk of methods that exploit relationships between action units is that the relationships can be very different accross datasets (e.g. AU6 can occur both in an expression of pain and in happiness, and this co-occurence will be very different in a positive salience dataset such as SEMAINE compared to something like UNBC pain dataset). This difference in correlation can already be seen in Figure 1 with quite different co-occurences of AU1 and AU12.