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ACM Multimedia 2023Technical Demonstrations

MobileVidFactory: Automatic Diffusion-Based Social Media Video Generation for Mobile Devices from Text

Junchen Zhu, Huan Yang 0005, Wenjing Wang 0001, Huiguo He, Zixi Tuo, Yongsheng Yu, Wen-Huang Cheng, Lianli Gao, Jingkuan Song, Jianlong Fu, Jiebo Luo 0001

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3581783.3612667 ↗

摘要

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 utilize the pretrained image diffusion model, and adapt it to a high-quality open-domain vertical video generator. 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 for enriching visual expression, and specify texts for automatic reading with optional voices as they like.