Micro-Expression Recognition Based On 3DCNN Combined With GRU and New Attention Mechanism

Micro-expressions, as a form of non-verbal emotional expressions, play a key role in interpersonal interaction. However, they are also quite challenging and not easy to analyze. In this paper, we propose a dual-branch shallow 3DCNN architecture that combines Gated Recurrent Unit (GRU) and enhances the Channel Attention Module (CAM) in Convolutional Block Attention Module (CBAM) to make it more suitable for recognizing micro facial expressions. Experiments show that the proposed method can achieve good results with a relatively simple architecture. The source code and pre-trained models are available at https://github.com/dannyFan-0201/ICIP_2024.