OAENet: Oriented attention ensemble for accurate facial expression recognition
作者：
Highlights：
• We propose a Oriented Attention Enable Network (OAENet) architecture for FER, which aggreates ROI aware and attention mechanism, ensuring the sufficient utilization of both global and local features.
• We propose a weighed mask that combines the facial landmarks and correlation coefficients coefficients, which prove to be effective to improve the attention on local regions.
• Our method has achieved state-of-the-art performances on several leading datasets such as Ck+, RAF-DB and AffectNet.
摘要
•We propose a Oriented Attention Enable Network (OAENet) architecture for FER, which aggreates ROI aware and attention mechanism, ensuring the sufficient utilization of both global and local features.•We propose a weighed mask that combines the facial landmarks and correlation coefficients coefficients, which prove to be effective to improve the attention on local regions.•Our method has achieved state-of-the-art performances on several leading datasets such as Ck+, RAF-DB and AffectNet.
论文关键词：Facial expression recognition,Weighted mask,Attention,Oriented gradient
论文评审过程：Received 17 November 2019, Revised 27 September 2020, Accepted 7 October 2020, Available online 17 October 2020, Version of Record 30 January 2021.
论文官网地址：https://doi.org/10.1016/j.patcog.2020.107694
