4 citations · 4 across the 6 of their papers we have counts for
10 papers · 1 filter
PhysiGen: Integrating Collision-Aware Physical Constraints for High-Fidelity Human-Human Interaction Generation
Nan Lei, Yuan-Ming Li, Ling-An Zeng +5
Despite substantial progress in text-driven 3D human motion synthesis, generating realistic multi-person interaction sequences remains challenging. Notably, body inter-penetration…
MotionHiFlow: Text-to-motion via hierarchical flow matching
Heng Li, Xiaotong Lin, Ling-An Zeng +3
Text-to-motion generation aims to generate 3D human motions that are tightly aligned with the input text while remaining physically plausible and rich in fine-grained detail. Altho…
IRG-MotionLLM: Interleaving Motion Generation, Assessment and Refinement for Text-to-Motion Generation
Yuan-Ming Li, Qize Yang, Nan Lei +5
Recent advances in motion-aware large language models have shown remarkable promise for jointly learning motion understanding and generation knowledge. However, these models typica…
Progressive Human Motion Generation Based on Text and Few Motion Frames
Ling-An Zeng, Gaojie Wu, Ancong Wu +2
Although existing text-to-motion (T2M) methods can produce realistic human motion from text description, it is still difficult to align the generated motion with the desired postur…
Efficient Explicit Joint-level Interaction Modeling with Mamba for Text-guided HOI Generation
Guohong Huang, Ling-An Zeng, Zexin Zheng +2
We propose a novel approach for generating text-guided human-object interactions (HOIs) that achieves explicit joint-level interaction modeling in a computationally efficient manne…
ChainHOI: Joint-based Kinematic Chain Modeling for Human-Object Interaction Generation
Ling-An Zeng, Guohong Huang, Yi-Lin Wei +4
We propose ChainHOI, a novel approach for text-driven human-object interaction (HOI) generation that explicitly models interactions at both the joint and kinetic chain levels. Unli…