49 citations · 72 across the 11 of their papers we have counts for
13 papers
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…
Rethinking Bimanual Robotic Manipulation: Learning with Decoupled Interaction Framework
Jian-Jian Jiang, Xiao-Ming Wu, Yi-Xiang He +4
Bimanual robotic manipulation is an emerging and critical topic in the robotics community. Previous works primarily rely on integrated control models that take the perceptions and…
AffordDexGrasp: Open-set Language-guided Dexterous Grasp with Generalizable-Instructive Affordance
Yi-Lin Wei, Mu Lin, Yuhao Lin +4
Language-guided robot dexterous generation enables robots to grasp and manipulate objects based on human commands. However, previous data-driven methods are hard to understand inte…
Light-T2M: A Lightweight and Fast Model for Text-to-motion Generation
Ling-An Zeng, Guohong Huang, Gaojie Wu +1
Despite the significant role text-to-motion (T2M) generation plays across various applications, current methods involve a large number of parameters and suffer from slow inference…
TechCoach: Towards Technical-Point-Aware Descriptive Action Coaching
Yuan-Ming Li, An-Lan Wang, Kun-Yu Lin +4
To guide a learner in mastering action skills, it is crucial for a coach to 1) reason through the learner's action execution and technical points (TechPoints), and 2) provide detai…
EgoExo-Fitness: Towards Egocentric and Exocentric Full-Body Action Understanding
Yuan-Ming Li, Wei-Jin Huang, An-Lan Wang +3
We present EgoExo-Fitness, a new full-body action understanding dataset, featuring fitness sequence videos recorded from synchronized egocentric and fixed exocentric (third-person)…
Multimodal Action Quality Assessment
Ling-An Zeng, Wei-Shi Zheng
Action quality assessment (AQA) is to assess how well an action is performed. Previous works perform modelling by only the use of visual information, ignoring audio information. We…
Continual Action Assessment via Task-Consistent Score-Discriminative Feature Distribution Modeling
Yuan-Ming Li, Ling-An Zeng, Jing-Ke Meng +1
Action Quality Assessment (AQA) is a task that tries to answer how well an action is carried out. While remarkable progress has been achieved, existing works on AQA assume that all…