This work is ranked 3rd place in the FME Challenge of ACM Multimedia 2021.
The project is the source code for the paper of «Facial Action Unit-based Deep Learning Framework for Spotting Macro- and Micro-expressions in Long Video Sequences», which is submitted to ACM Multimedia 2021 as for FME Challenge 2021. You can also find this paper from Researchgate.
Note that anyone using this project should cite the following paper：
@Inbook{10.1145/3474085.3479209,
author = {Yang, Bo and Wu, Jianming and Zhou, Zhiguang and Komiya, Megumi and Kishimoto, Koki and Xu, Jianfeng and Nonaka, Keisuke and Horiuchi, Toshiharu and Komorita, Satoshi and Hattori, Gen and Naito, Sei and Takishima, Yasuhiro},
title = {Facial Action Unit-Based Deep Learning Framework for Spotting Macro- and Micro-Expressions in Long Video Sequences},
year = {2021},
isbn = {9781450386517},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
booktitle = {Proceedings of the 29th ACM International Conference on Multimedia},
pages = {4794–4798},
numpages = {5}
}Questions and comments can be sent to:
Jianming Wu(ji-wu@kddi-research.jp) or Bo Yang(bo-yang@kddi-research.jp)
The following papers are also related to this work:
@article{YANG202363,
title = {Deep Learning Pipeline for Spotting Macro- and Micro-expressions in Long Video Sequences Based on Action Units and Optical Flow},
journal = {Pattern Recognition Letters},
volume = {165},
pages = {63-74},
year = {2023},
issn = {0167-8655},
author = {Bo Yang and Jianming Wu and Kazushi Ikeda and Gen Hattori and Masaru Sugano and Yusuke Iwasawa and Yutaka Matsuo},
keywords = {deep learning, macro-expression, micro-expression, action units, optical flow},
}