6 papers
Making Avatars Interact: Towards Text-Driven Human-Object Interaction for Controllable Talking Avatars
Youliang Zhang, Zhengguang Zhou, Zhentao Yu +11
Generating talking avatars is a fundamental task in video generation. Although existing methods can generate full-body talking avatars with simple human motion, extending this task…
SpeechJudge: Towards Human-Level Judgment for Speech Naturalness
Xueyao Zhang, Chaoren Wang, Huan Liao +8
Aligning large generative models with human feedback is a critical challenge. In speech synthesis, this is particularly pronounced due to the lack of a large-scale human preference…
X-NeMo: Expressive Neural Motion Reenactment via Disentangled Latent Attention
Xiaochen Zhao, Hongyi Xu, Guoxian Song +6
We propose X-NeMo, a novel zero-shot diffusion-based portrait animation pipeline that animates a static portrait using facial movements from a driving video of a different individu…
SpeakerVid-5M: A Large-Scale High-Quality Dataset for Audio-Visual Dyadic Interactive Human Generation
Youliang Zhang, Zhaoyang Li, Duomin Wang +6
The rapid development of large-scale models has catalyzed significant breakthroughs in the digital human domain. These advanced methodologies offer high-fidelity solutions for avat…
A Plug-and-Play Physical Motion Restoration Approach for In-the-Wild High-Difficulty Motions
Youliang Zhang, Ronghui Li, Yachao Zhang +4
Extracting physically plausible 3D human motion from videos is a critical task. Although existing simulation-based motion imitation methods can enhance the physical quality of dail…
InterDance:Reactive 3D Dance Generation with Realistic Duet Interactions
Ronghui Li, Youliang Zhang, Yachao Zhang +6
Humans perform a variety of interactive motions, among which duet dance is one of the most challenging interactions. However, in terms of human motion generative models, existing w…