Facial Expression Recognition Based on Region Enhanced Attention Network
In order to recognize facial expression images in real environments including complex back-ground,facial occlusion and other factors,a facial expression recognition method based on region enhanced attention network is proposed.Firstly,an attention-based region enhancement network is proposed to reduce the influence of external factors and enhance the robustness of expression recognition in real environments.Then,a channel-spatial attention fusion network is proposed to extract global features.Finally,the recogni-tion degree of facial expression images is improved by the combination of partition loss and cross entropy loss,thereby improving the recognition accuracy.The experimental results on the public datasets RAF-DB,FERPlus and AffectNet show that their expression recognition accuracy is 88.81%,89.32%and 60.45%.In conclusion,the method in this paper has good accuracy and robustness.
facial expression recognitionregional enhancementattention fusionpartition loss
万方数据
维普
