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Bei-Bei Jing

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Preprint Sep 2026

MoVT: Video-Augmented Motion Tokenizer for Text-to-Motion Generation

Text-driven 3D human motion generation models face significant challenges in responding to diverse and unconstrained textual prompts, primarily due to the limited availability of 3D motion training data. To address this, we introduce MoVT, a novel framework that effectively leverages the extensive range of human action...

Bei-Bei Jing, Tian-Le Guo, You-Jia Zhang et al. · 0 citations
Preprint Aug 2026

UniMoFlow: Grounding Instruction-Driven 3D Human Motion Editing in Generation

A closed-loop synthesis-and-verification pipeline that produces Omni-MoEdit, a large-scale dataset spanning body-part, amplitude, temporal, action, and style edits, and a unified latent flow-matching model that shares broad semantic and kinematic knowledge between generation and editing is developed.

Yilei Hua, Bei-Bei Jing, Ce Zheng et al. · 0 citations

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