Jingyu Xiang

2 accepted papers

2026

LaMoGen: Language to Motion Generation Through LLM-Guided Symbolic Inference

Junkun Jiang, Ho Yin Au, Jingyu Xiang, Jie Chen

CVPR 2026

Human motion is highly expressive and naturally aligned with language, yet prevailing methods relying heavily on joint text-motion embeddings struggle to synthesize temporally accurate, detailed motions and often lack explainability. To address these limitations, we introduce LabanLite, a motion rep

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2025

Deep Compositional Phase Diffusion for Long Motion Sequence Generation

Ho Yin Au, Jie Chen, Junkun Jiang, Jingyu Xiang

NeurIPS 2025oral

Recent research on motion generation has shown significant progress in generating semantically aligned motion with singular semantics. However, when employing these models to create composite sequences containing multiple semantically generated motion clips, they often struggle to preserve the conti…

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