The development of convolutional neural networks has greatly promoted the advancement of facial expression recognition technology. In order to solve the problem that the accuracy of image recognition in practical applications is limited by image pixels, the expression recognition of low pixel face image is studied from three aspects. First, according to the characteristics of low pixels and complex features of the research object, an improved convolutional neural network is proposed. Second, after performing basic pre-processing on the image, image enhancement processing is added as an input to improve the convolutional neural network mode. Finally, the output results of the model are subjected to decision fusion to obtain the final recognition result. Experimental results show that this method has achieved good results on the CK+ source dataset, and has high recognition accuracy, stable results, and strong generalization ability.