6 papers
TurboTalk: Progressive Distillation for One-Step Audio-Driven Talking Avatar Generation
Xiangyu Liu, Feng Gao, Xiaomei Zhang +4
Existing audio-driven video digital human generation models rely on multi-step denoising, resulting in substantial computational overhead that severely limits their deployment in r…
TAMISeg: Text-Aligned Multi-scale Medical Image Segmentation with Semantic Encoder Distillation
Qiang Gao, Yi Wang, Yong Zhang +4
Medical image segmentation remains challenging due to limited fine-grained annotations, complex anatomical structures, and image degradation from noise, low contrast, or illuminati…
WildActor: Unconstrained Identity-Preserving Video Generation
Qin Guo, Tianyu Yang, Xuanhua He +5
Production-ready human video generation requires digital actors to maintain strictly consistent full-body identities across dynamic shots, viewpoints and motions, a setting that re…
MAViD: A Multimodal Framework for Audio-Visual Dialogue Understanding and Generation
Youxin Pang, Jiajun Liu, Lingfeng Tan +6
We propose MAViD, a novel Multimodal framework for Audio-Visual Dialogue understanding and generation. Existing approaches primarily focus on non-interactive systems and are limite…
U-Mind: A Unified Framework for Real-Time Multimodal Interaction with Audiovisual Generation
Xiang Deng, Feng Gao, Yong Zhang +5
Full-stack multimodal interaction in real-time is a central goal in building intelligent embodied agents capable of natural, dynamic communication. However, existing systems are ei…
UniMo: Unifying 2D Video and 3D Human Motion with an Autoregressive Framework
Youxin Pang, Yong Zhang, Ruizhi Shao +5
We propose UniMo, an innovative autoregressive model for joint modeling of 2D human videos and 3D human motions within a unified framework, enabling simultaneous generation and und…