Generative steganography hides secret messages by generating sufficiently natural or true samples with secret，which is a hot research topic in information hiding， but there is little research in the field of video steganography. Combined with the idea of digital Cardan grille， a semi-generative video steganography scheme based on Deep Convolutional Generative Adversarial Net （DCGAN） was proposed. In this scheme， a dual-stream video generation network based on DCGAN was designed to generate three parts of videos： dynamic foreground， static background and spatio-temporal mask， and different videos were produced by the generation network driven by random noise. The sender in this scheme was able to set the steganography threshold and adaptively generate a digital Cardan grille in the mask， then the obtain digital cardan grille was used as the key for steganography and extraction； at same time， with the foreground as the carrier， the optimal embedding of information was realized. Experimental results show that the video-with-secret generated by the proposed scheme has good visual quality， with a Frechet Inception Distance score （FID） of 90， and the embedding capacity of the scheme is better than those of the existing generative steganography schemes， up to 0.11 bpp. It can be seen that the proposed scheme can transmit secret messages more efficiently.