collaborators

8 papers

cs.CV2026

StreamAvatar: Streaming Diffusion Models for Real-Time Interactive Human Avatars

Zhiyao Sun, Ziqiao Peng, Yifeng Ma +8

Real-time, streaming interactive avatars represent a critical yet challenging goal in digital human research. Although diffusion-based human avatar generation methods achieve remar…

cs.CV2026

UniAVGen: Unified Audio and Video Generation with Asymmetric Cross-Modal Interactions

Guozhen Zhang, Zixiang Zhou, Teng Hu +6

Due to the lack of effective cross-modal modeling, existing open-source audio-video generation methods often exhibit compromised lip synchronization and insufficient semantic consi…

cs.CV2026

HYDRA: Unifying Multi-modal Generation and Understanding via Representation-Harmonized Tokenization

Xuerui Qiu, Yutao Cui, Guozhen Zhang +9

Unified Multimodal Models struggle to bridge the fundamental gap between the abstract representations needed for visual understanding and the detailed primitives required for gener…

cs.CV2026

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…

cs.CV2026

ActAvatar: Temporally-Aware Precise Action Control for Talking Avatars

Ziqiao Peng, Yi Chen, Yifeng Ma +10

Despite significant advances in talking avatar generation, existing methods face critical challenges: insufficient text-following capability for diverse actions, lack of temporal a…

cs.CV2026

Video Generation Models Are Good Latent Reward Models

Xiaoyue Mi, Wenqing Yu, Jiesong Lian +9

Reward feedback learning (ReFL) has proven effective for aligning image generation with human preferences. However, its extension to video generation faces significant challenges.…