Paper ID: 2303.09293

A transformer-based approach to video frame-level prediction in Affective Behaviour Analysis In-the-wild

Dang-Khanh Nguyen, Ngoc-Huynh Ho, Sudarshan Pant, Hyung-Jeong Yang

In recent years, transformer architecture has been a dominating paradigm in many applications, including affective computing. In this report, we propose our transformer-based model to handle Emotion Classification Task in the 5th Affective Behavior Analysis In-the-wild Competition. By leveraging the attentive model and the synthetic dataset, we attain a score of 0.4775 on the validation set of Aff-Wild2, the dataset provided by the organizer.

Submitted: Mar 16, 2023