The invention discloses a multi-scale generative adversarial network-based shielded pedestrian re-identification method, and relates to a computer vision technology. The method comprises the followingsteps of preparing a pedestrian image training set; designing and training a multi-scale generative adversarial network, with the network comprising a multi-scale generator and a discriminator, withthe multi-scale generator being capable of performing a de-occlusion operation on the random occlusion area to generate a high-quality reconstructed graph; enabling a discriminator to distinguish whether the input image is a real image or a generated image; generating an expanded pedestrian image training set by using the trained multi-scale generator; designing and training a classification recognition network, wherein the network is used for performing identity classification on the input pedestrian images; and extracting features of the pedestrian images by using the trained classificationand recognition network and carrying out similarity matching.