Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

We address the problem of generating diverse 3D human motions from textual descriptions.
This challenging task requires joint modeling of both modalities: understanding and …

Generating talking head videos through a face image and a piece of speech audio still
contains many challenges. ie, unnatural head movement, distorted expression, and identity …

Virtual human is widely employed in various industries, including personal assistance,
intelligent customer service, and online education, thanks to the rapid development of …

In this work, we tackle the challenge of enhancing the realism and expressiveness in talking
head video generation by focusing on the dynamic and nuanced relationship between audio …

This work addresses the problem of generating 3D holistic body motions from human
speech. Given a speech recording, we synthesize sequences of 3D body poses, hand …

Speech-driven 3D facial animation has been widely studied, yet there is still a gap to
achieving realism and vividness due to the highly ill-posed nature and scarcity of audio …

Visual speech, referring to the visual domain of speech, has attracted increasing attention
due to its wide applications, such as public security, medical treatment, military defense, and …

Speech-driven 3D face animation aims to generate realistic facial expressions that match
the speech content and emotion. However, existing methods often neglect emotional facial …

Talking face generation, also known as speech-to-lip generation, reconstructs facial motions
concerning lips given coherent speech input. The previous studies revealed the importance …