A large-pose face recognition method, comprising: learning a first image feature of a face training image by means of a texture learning network (S101); reconstructing a corresponding three-dimensional face according to the face training image, and converting shape information of the reconstructed three-dimensional face into a two-dimensional texture image (S102); learning a second image feature of the two-dimensional texture image by means of a shape learning network (S103); and combining the first image feature and the second image feature to recognize a face (S104). A two-dimensional planar feature and a three-dimensional feature can be expressed in a combined manner, such that the accuracy of large-pose face recognition is effectively improved. In addition, a training process is relatively simple, and the occupation of a storage space can be reduced.
LARGE-POSE FACE RECOGNITION METHOD AND APPARATUS, AND DEVICE