4 papers
HumanCLAW: Can Vision-Language Models Act Through a Body?
Siyao Li, Li Siyao, Jiawei Gu +16
The paper introduces HumanCLAW, a framework that separates decision making of vision‑language models from low‑level motor execution, allowing evaluation of a model's action intelli…
LLaMo: Scaling Pretrained Language Models for Unified Motion Understanding and Generation with Continuous Autoregressive Tokens
Zekun Li, Sizhe An, Chengcheng Tang +7
Recent progress in large models has led to significant advances in unified multimodal generation and understanding. However, the development of models that unify motion-language ge…
EgoPoseFormer v2: Accurate Egocentric Human Motion Estimation for AR/VR
Zhenyu Li, Sai Kumar Dwivedi, Filip Maric +11
Egocentric human motion estimation is essential for AR/VR experiences, yet remains challenging due to limited body coverage from the egocentric viewpoint, frequent occlusions, and…
Geometric Neural Distance Fields for Learning Human Motion Priors
Zhengdi Yu, Simone Foti, Linguang Zhang +4
We introduce Neural Riemannian Motion Fields (NRMF), a novel 3D generative human motion prior that enables robust, temporally consistent, and physically plausible 3D motion recover…