论文标题
基于转移学习的面部动作单位识别
Facial Action Unit Recognition Based on Transfer Learning
论文作者
论文摘要
面部动作单位识别是面部分析的重要任务。由于复杂的收集环境，野外的面部动作单元识别仍然具有挑战性。关于情感行为分析（ABAW）的第三次竞争（ABAW）提供了大量的面部图像，并提供了面部动作单位注释。在本文中，我们介绍了一种基于转移学习的面部动作单元识别方法。我们首先使用带有表达标签的可用面部图像来训练特征提取网络。然后，我们微调了面部动作单元识别网络。
Facial action unit recognition is an important task for facial analysis. Owing to the complex collection environment, facial action unit recognition in the wild is still challenging. The 3rd competition on affective behavior analysis in-the-wild (ABAW) has provided large amount of facial images with facial action unit annotations. In this paper, we introduce a facial action unit recognition method based on transfer learning. We first use available facial images with expression labels to train the feature extraction network. Then we fine-tune the network for facial action unit recognition.
