English

Facial Expression Recognition based on Multi-head Cross Attention Network

Computer Vision and Pattern Recognition 2022-03-25 v1

Abstract

Facial expression in-the-wild is essential for various interactive computing domains. In this paper, we proposed an extended version of DAN model to address the VA estimation and facial expression challenges introduced in ABAW 2022. Our method produced preliminary results of 0.44 of mean CCC value for the VA estimation task, and 0.33 of the average F1 score for the expression classification task.

Keywords

Cite

@article{arxiv.2203.13235,
  title  = {Facial Expression Recognition based on Multi-head Cross Attention Network},
  author = {Jae-Yeop Jeong and Yeong-Gi Hong and Daun Kim and Yuchul Jung and Jin-Woo Jeong},
  journal= {arXiv preprint arXiv:2203.13235},
  year   = {2022}
}
R2 v1 2026-06-24T10:25:00.275Z