Abstract: The present disclosure provides a training method of a facial expression embedding model, a facial expression embedding method, and a facial expression embedding device. The method includes: determining a sample set, wherein each sample in the sample set includes three images and a sample label; and training the to-be-trained facial expression embedding model with the sample set, to obtain the trained facial expression embedding model, wherein the to-be-trained facial expression embedding model includes a to-be-trained full face embedding sub-model and a trained identity embedding sub-model, the trained facial expression embedding model includes a trained full face embedding sub-model and the trained identity embedding sub-model, and an output of the trained facial expression embedding model is determined by a difference between an output of the trained full face embedding sub-model and an output of the trained identity embedding sub-model.