Sequential Models for Automatic Personality Recognition from Multimodal Information in Social Interactions

We study the problem of recognizing personality from videos depicting users' social interaction. Multimodal information is represented using pretrained models, and multi-stream sequential models are considered for prediction. Experimental results of the proposed method in the recently released UDIVA dataset are reported and compared to related work. We show that the proposed methodology is competitive with the state-of-the-art while using less complex models.