MobileVidFactory: Automatic Diffusion-Based Social Media Video
  Generation for Mobile Devices from Text
Junchen Zhu Huan Yang Wenjing Wang Huiguo He Zixi Tuo Yongsheng Yu Wen-Huang Cheng Lianli Gao Jingkuan Song Jianlong Fu Jiebo Luo
Videos for mobile devices become the most popular access to share and acquire
information recently. For the convenience of users' creation, in this paper, we
present a system, namely MobileVidFactory, to automatically generate vertical
mobile videos where users only need to give simple texts mainly. Our system
consists of two parts: basic and customized generation. In the basic
generation, we take advantage of the pretrained image diffusion model, and
adapt it to a high-quality open-domain vertical video generator for mobile
devices. As for the audio, by retrieving from our big database, our system
matches a suitable background sound for the video. Additionally to produce
customized content, our system allows users to add specified screen texts to
the video for enriching visual expression, and specify texts for automatic
reading with optional voices as they like.