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arXiv · 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
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Abstract

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.

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Dang-Khanh Nguyen, Ngoc-Huynh Ho, Sudarshan Pant, Hyung-Jeong Yang. 2023-03-16. A transformer-based approach to video frame-level prediction in Affective Behaviour Analysis In-the-wild. https://arxiv.org/abs/2303.09293

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