Aiming at the problems in the active terahertz (THz) imaging such as the poor image quality,the variety of hidden objects and the scarcity and imbalance of training samples, the objects segmentation networks based on the conditional generative adversarial networks′model Mask-CGANs and the objects detection and recognition networks based on the RetinaNet are built, which realizes the multi-object segmentation, detection and recognition of hidden objects in the THz imaging. The constraint loss functions and the networks structures proposed for the segmentation task make the model keep the balance between the recall rate and the false alarm rate, and the requirement of training sample size is reduced. The loss functions used for the detection task improve the detection accuracy under the condition of unbalanced training samples.