Zero-shot Compound Expression Recognition with Visual Language Model at the 6th ABAW Challenge

Understand

Conventional approaches to facial expression recognition primarily focus on the classification of six basic facial expressions.

• Nevertheless, real-world situations present a wider range of complex compound expressions that consist of combinations of these basics ones due to limited availability of comprehensive training datasets.
• The 6th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW) offered unlabeled datasets containing compound expressions.
• In this study, we propose a zero-shot approach for recognizing compound expressions by leveraging a pretrained visual language model integrated with some traditional CNN networks.