现有的深度神经网络隐写检测技术主要针对数字图像隐写，但视频隐写与图像隐写存在很大差异，因此无法将用于图像隐写分析的深度神经网络直接用于视频隐写分析。为此，文中以修改运动向量的视频隐写为检测对象，在新型图像隐写分析网络SRNet基础上，设计了一种用于视频隐写检测的深度神经网络，构造了能准确反映运动向量隐写修改的输入矩阵。实验结果表明，文中提出的方法对中低码率的视频检测准确率明显高于两种传统的视频隐写分析方法，且对不同码率的视频检测性能平稳。

The existing deep neural network steganography detection technology was mainly proposed for digital image steganography． Since there are great differences between image steganography and video steganography，the deep neural networks designed for image steganalysis cannot be simply extended to video steganalysis． Therefore，a motion vector-modification video steganography was taken as the target example and a deep neural network for video steganalysis was proposed based on state-of-the-art image steganalysis network SＲNet． A data input matrix which can well reflect the steganographic modification of motion vectors was also introduced． Experimental results demon-strate that the proposed method outperforms two traditional video steganalysis algorithms in detection accuracy for low and middle-bitrate videos，and behaves well for videos at different bitrates．