English

An Audio-Video Deep and Transfer Learning Framework for Multimodal Emotion Recognition in the wild

Machine Learning 2020-11-03 v3 Sound Audio and Speech Processing

Abstract

In this paper, we present our contribution to ABAW facial expression challenge. We report the proposed system and the official challenge results adhering to the challenge protocol. Using end-to-end deep learning and benefiting from transfer learning approaches, we reached a test set challenge performance measure of 42.10%.

Keywords

Cite

@article{arxiv.2010.03692,
  title  = {An Audio-Video Deep and Transfer Learning Framework for Multimodal Emotion Recognition in the wild},
  author = {Denis Dresvyanskiy and Elena Ryumina and Heysem Kaya and Maxim Markitantov and Alexey Karpov and Wolfgang Minker},
  journal= {arXiv preprint arXiv:2010.03692},
  year   = {2020}
}

Comments

Results on test dataset and acknowledgements were added

R2 v1 2026-06-23T19:09:04.133Z