activity
20242026
most citedControllable Video Generation: A Survey

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

SignGPT: Toward LLM-Mediated Sign Language Interaction through Gloss-Free Translation and Generation

Ronghui Li, Jun Dong, Zhongyuan Hu +8

Large language models (LLMs) provide limited support for sign language interaction. Unifying sign language translation (SLT) and generation (SLG) to enable sign language as both in…

cs.CV2026

InfiniteDance: Scalable 3D Dance Generation Towards in-the-wild Generalization

Ronghui Li, Zhongyuan Hu, Li Siyao +6

Although existing 3D dance generation methods perform well in controlled scenarios, they often struggle to generalize in the wild. When conditioned on unseen music, existing method…

cs.CV2025

WATCH: World-aware Allied Trajectory and pose reConstruction for Camera and Human

Qijun Ying, Zhongyuan Hu, Rui Zhang +5

Reconstructing global human motion from monocular video is fundamental to VR, graphics, and robotics, yet remains ill-posed due to depth ambiguity, motion ambiguity, and the entang…

cs.GR2025★ 1 cited

Controllable Video Generation: A Survey

Yue Ma, Kunyu Feng, Zhongyuan Hu +19

With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video…

cs.CV2024

AToM: Aligning Text-to-Motion Model at Event-Level with GPT-4Vision Reward

Haonan Han, Xiangzuo Wu, Huan Liao +5

Recently, text-to-motion models have opened new possibilities for creating realistic human motion with greater efficiency and flexibility. However, aligning motion generation with…