Affective Expression Analysis in-the-wild using Multi-Task Temporal Statistical Deep Learning Model [article]

Nhu-Tai Do, Tram-Tran Nguyen-Quynh, Soo-Hyung Kim
2020 arXiv   pre-print
Affective behavior analysis plays an important role in human-computer interaction, customer marketing, health monitoring. ABAW Challenge and Aff-Wild2 dataset raise the new challenge for classifying basic emotions and regression valence-arousal value under in-the-wild environments. In this paper, we present an affective expression analysis model that deals with the above challenges. Our approach includes STAT and Temporal Module for fine-tuning again face feature model. We experimented on
more » ... ld2 dataset, a large-scale dataset for ABAW Challenge with the annotations for both the categorical and valence-arousal emotion. We achieved the expression score 0.543 and valence-arousal score 0.534 on the validation set.
arXiv:2002.09120v3 fatcat:ojaxz47zpzakjc7tam7y664ceu