Automatic recognition of handwritten Chinese has a wide range of applications in document digitization and handwritten note transcription. A method based on attention mechanism is proposed to recognize the handwritten Chinese characterized by their random writing, complex structure, and large number of features. Based on the traditional convolutional neural network (CNN) model, an attention-CNN (AT-CNN) model is proposed. The information interaction between each layer in the network is realized using attention mechanism, thus the information loss caused by pooling operations reduces. Experiments on the classical handwritten Chinese data set HWDB show that the recognition accuracy of this method can reach 95.05%, which is significantly improved compared with that by other models.