# Transfer Learning for Action Unit Recognition

arXiv: https://arxiv.org/abs/1807.07556 · HTML: https://mlsanity.com/paper/1807.07556/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jul 2018.

## Built on by (most cited first, 2 of 2)

- [Baby Physical Safety Monitoring in Smart Home Using Action Recognition System](https://mlsanity.com/paper/2210.12527/) (2022)
- [ML4ML: Automated Invariance Testing for Machine Learning Models](https://mlsanity.com/paper/2109.12926/) (2021)

## Abstract (arXiv)

This paper presents a classifier ensemble for Facial Expression Recognition (FER) based on models derived from transfer learning. The main experimentation work is conducted for facial action unit detection using feature extraction and fine-tuning convolutional neural networks (CNNs). Several classifiers for extracted CNN codes such as Linear Discriminant Analysis (LDA), Support Vector Machines (SVMs) and Long Short-Term Memory (LSTM) are compared and evaluated. Multi-model ensembles are also used to further improve the performance. We have found that VGG-Face and ResNet are the relatively optimal pre-trained models for action unit recognition using feature extraction and the ensemble of VGG-Net variants and ResNet achieves the best result.