Social media plays an increasingly important role in providing information and social support to users. Due to the easy dissemination of content, as well as difficulty to track on the social network, we are motivated to study the way of concealing sensitive messages in this channel with high confidentiality. In this paper, we design a steganographic visual stories generation model that enables users to automatically post stego status on social media without any direct user intervention and use the mutual-perceived joint attention (MPJA) to maintain the imperceptibility of stego text. We demonstrate our approach on the visual storytelling (VIST) dataset and show that it yields high-quality steganographic texts. Since the proposed work realizes steganography by auto-generating visual story using deep learning, it enables us to move steganography to the real-world online social networks with intelligent steganographic bots.

社交媒体在向用户提供信息和社交支持方面扮演着越来越重要的角色。由于内容的易于分发以及在社交网络上的跟踪困难，我们被激励研究以高度机密性在此渠道中隐藏敏感消息的方法。在本文中，我们设计了一种隐写视觉故事生成模型，该模型使用户无需任何直接用户干预即可在社交媒体上自动发布隐身状态，并使用相互感知的共同注意（MPJA）来保持隐身文本的隐蔽性。我们在视觉故事（VIST）数据集上展示了我们的方法，并表明它可以产生高质量的隐写文字。由于拟议的工作通过使用深度学习自动生成视觉故事来实现隐写术，