A multi-modal fusion technology based infrared face recognition method is proposed to address the cur- rent issue of low accuracy in infrared human recognition. Perform denoising and enhancement processing on facial ima- ges to obtain high grayscale images. Use two-dimensional wavelet transform to extract concatenated feature vectors, and use multimodal fusion algorithm to calculate the contextual attention coefficient of feature channels to quantify fea- ture differences between classes. Combined with modal fusion decision functions, fuse facial image features and calcu- late the matching degree between images based on the optimal classification criteria of the classifier, achieving infrared facial recognition. In the experimental demonstration, the recognition performance of the proposed method was veri- fied, and the results showed that in the recognition of large and small samples, the recognition accuracy obtained by the proposed method was about 95%, which has a high recognition accuracy for infrared facial images.