Coherence and identity learning for arbitrary-length face video generation

• Main Authors: YE, Shuquan, HAN, Chu, LIN, Jiaying, HAN, Guoqiang, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Interpolation; Cascaded networks; Coherence networks; Divide and conquer; Generative model; State of the art; Three component; Video generation; Visual qualities; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8438; https://ink.library.smu.edu.sg/context/sis_research/article/9441/viewcontent/Ye_2020_facevideo.pdf
• Institution: Singapore Management University

Face synthesis is an interesting yet challenging task in computer vision. It is even much harder to generate a portrait video than a single image. In this paper, we propose a novel video generation framework for synthesizing arbitrary-length face videos without any face exemplar or landmark. To over...