@inproceedings{6852492cc7194ffba3a27ed04427958f,
title = "Dual-stream Shallow Networks for Facial Micro-expression Recognition",
abstract = "Micro-expressions are spontaneous, brief and subtle facial muscle movements that exposes underlying emotions. Motivated by recent exploits into deep learning for micro-expression analysis, we propose a lightweight dual-stream shallow network in the form of a pair of truncated CNNs with heterogeneous input features. The merging of the convolutional features allows for discriminative learning of micro-expression classes stemming from both streams. Using activation heatmaps, we further demonstrate that salient facial areas are well emphasized, and correspond closely to relevant action units belonging to emotion classes. We empirically validate the proposed network on three benchmark databases, obtaining state-of-the-art performance on the CASME II and SAMM while remaining competitive on the SMIC. Further observations point towards the sufficiency of utilizing shallower deep networks for micro-expression recognition.",
keywords = "apex frame, dual-stream networks, Micro-expression, recognition, shallow CNN",
author = "Huai-Qian Khor and John See and Sze-Teng Liong and Phan, {Raphael C. W.} and Weiyao Lin",
note = "Funding Information: This work is supported in part by MOHE Grant FRGS/1/2016/ICT02/ MMU/02/2 Malaysia and Shanghai {\textquoteright}The Belt and Road{\textquoteright} Young Scholar Exchange Grant (17510740100). Funding Information: This work was funded in part by MOHE Grant FRGS/1/2016/ ICT02/MMU/02/2 Malaysia and Shanghai {\textquoteright}The Belt and Road{\textquoteright} Young Scholar Exchange Grant (17510740100). Publisher Copyright: {\textcopyright} 2019 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 26th IEEE International Conference on Image Processing 2019, ICIP 2019 ; Conference date: 22-09-2019 Through 25-09-2019",
year = "2019",
month = aug,
day = "26",
doi = "10.1109/ICIP.2019.8802965",
language = "English",
series = "International Conference on Image Processing",
publisher = "IEEE",
pages = "36--40",
booktitle = "2019 IEEE International Conference on Image Processing (ICIP)",
address = "United States",
}