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STCAM: Spatial-Temporal and Channel Attention Module for Dynamic Facial Expression Recognition by Weicong Chen; Dong Zhang; Ming Li; Dah-Jye Lee is a Psychology article available to read on EtoBox.

What is STCAM: Spatial-Temporal and Channel Attention Module for Dynamic Facial Expression Recognition about?

Capturing the dynamics of facial expression progression in video is an essential and challenging task for facial expression recognition (FER). In this paper, we propose an effective framework to address this challenge. We develop a C3Dbased network architecture, 3D-Inception-ResNet, to extract spatial-temporal features from the dynamic facial expression image sequence. A Spatial-Temporal and Channel Attention Module (STCAM) is proposed to explicitly exploit the holistic spatialtemporal and channel-wise correlations among the extracted features. Specifically, the proposed STCAM calculates a channelwise and a spatial-temporal-wise attention map to enhance the features along the corresponding feature dimensions for more representative features. We evaluate our method on three popular dynamic facial expression recognition datasets, CK+, Oulu-CASIA and MMI. Experimental results show that our method achieves better or comparable performance compared to the stateof-the-art approaches.

Who reads STCAM: Spatial-Temporal and Channel Attention Module for Dynamic Facial Expression Recognition?

Author

Weicong Chen; Dong Zhang; Ming Li; Dah-Jye Lee

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2023

Language

EN

Field

Psychology (Social Sciences)