The invention provides an automatic micro-expression identification method of a macro-to-micro conversion model based on depth learning. The method comprises steps that A, micro-expression sample processing, 1), a micro-expression data set sample and a macro-expression data set sample are pre-processed; 2), sample pairs of a cross-modal tuple loss function are constructed; B, cross-modal macro-to-micro conversion model training, 3), the AU detection network is trained, an AU detection network parameter is initialized, and a flexible maximum value loss function is trained; 4), the AU detection network parameter is fixed, a cross-modal macro-to-micro conversion model parameter is initialized, and the cross-modal macro-to-micro conversion model is trained; and C, micro-expression identification, according to a trained convolutional neural network model, a test parameter is initialized, a test sample is inputted to the trained convolutional neural network model, and an identification rate is outputted after forward network propagation. The method is advantaged in that robustness is realized compared with methods in the prior art.