Zhumei Wang — accepted AI-conference papers

2026

Mocap-2-to-3: Multi-view Lifting for Monocular Motion Recovery with 2D Pretraining

Zhumei Wang, Zechen Hu, Ruoxi Guo, Huaijin Pi, Ziyong Feng, Liang Zhang +2

CVPR 2026

Human motion recovery for real-world interaction demands both precise action details and metric-scale trajectories. Recovering absolute human pose from monocular input presents a viable solution, but faces two main challenges: (1) models' reliance on 3D training data from constrained environments li

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2025

Motion-2-to-3: Leveraging 2D Motion Data for 3D Motion Generations

Ruoxi Guo, Huaijin Pi, Zehong Shen, Qing Shuai, Zechen Hu, Zhumei Wang +5

ICCV 2025poster

Text-driven human motion synthesis has showcased its potential for revolutionizing motion design in the movie and game industry.Existing methods often rely on 3D motion capture data, which requires special setups, resulting in high costs for data acquisition, ultimately limiting the diversity and sc…

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