Year: 2022
Type: conference-paper
Abstract: This paper reports our solution for ACM Multimedia ViCo 2022 Conversational Head Generation Challenge, which aims to generate vivid face-to-face conversation videos based on audio and reference images. Our solution focuses on training a generalized audio-to-head driver using regularization and assembling a high visual quality renderer. We carefully tweak the audio-to-behavior model and post-process the generated video using our foreground-background fusion module. We get first place in the listening head generation track and second place in the talking head generation track in the official leaderboard. Our code is available at https://github.com/megvii-research/MM2022-ViCoPerceptualHeadGeneration.
Authors: Ailin Huang, Zhewei Huang, Shuchang Zhou
Institution: Megvii (China)
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4283710679