April 22, 2024, 4:42 a.m. | Yixiang Zhuang, Baoping Cheng, Yao Cheng, Yuntao Jin, Renshuai Liu, Chengyang Li, Xuan Cheng, Jing Liao, Juncong Lin

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.12888v1 Announce Type: cross
Abstract: Speech-driven facial animation methods usually contain two main classes, 3D and 2D talking face, both of which attract considerable research attention in recent years. However, to the best of our knowledge, the research on 3D talking face does not go deeper as 2D talking face, in the aspect of lip-synchronization (lip-sync) and speech perception. To mind the gap between the two sub-fields, we propose a learning framework named Learn2Talk, which can construct a better 3D …

abstract animation arxiv attention best of cs.cv cs.gr cs.lg face however knowledge research speech type

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Lead Data Scientist, Commercial Analytics

@ Checkout.com | London, United Kingdom

Data Engineer I

@ Love's Travel Stops | Oklahoma City, OK, US, 73120