Multi-modal target detection method and system suitable for modal deficiency

The invention discloses a multi-modal target detection method and system suitable for modal missing. The method comprises the following steps: S1, training a neural network unit by using multi-modal data in a data set; inputting all modal data of the data set into the trained neural network unit for detection, and storing a detection result; s2, extracting modal data of other dimensions; generating a pseudo-modal feature tensor by using the generative network unit, splicing, and inputting into the attention network unit, the information fusion unit and the discrimination network unit until the training of the generative network unit is completed; and S3, collecting modal data in real time through data collection equipment, and generating the type and identifier of the target by using the trained neural network unit. According to the method, on the premise that noise introduction and feature information loss are avoided, missing modal data are virtually generated, the calculation amount and complexity of the model are reduced to a great extent, and the representation consistency of generated modals can be improved.