6 papers
Unified Motion Retargeting for Humanoids with Learned Point Cloud Correspondence
Hanyang Cao, Yuetong Fang, Taesoo Kwon +10
Humanoid learning increasingly relies on transforming vast and diverse human motion data into high-quality robot reference trajectories. However, retargeting human motion to humano…
PFM-HR: Pose Flow Matching for Humanoid Robots
Yukang Gao, Yi Gu, Yangchen Zhou +9
Motion priors improve reinforcement learning for physics-based humanoid tracking, but temporal priors require ordered motion clips, while pose priors provide limited guidance for p…
Learning Context-Aware Motion Priors for Humanoid Control
Yunyang Mo, Yi Gu, Yangchen Zhou +2
Motion priors provide powerful guidance for learning naturalistic humanoid behaviors. However, existing methods typically learn a general, task-agnostic prior from the entire refer…
PDF-HR: Pose Distance Fields for Humanoid Robots
Yi Gu, Yukang Gao, Yangchen Zhou +7
Pose and motion priors play a crucial role in humanoid robotics. Although such priors have been widely studied in human motion recovery (HMR) domain with a range of models, their a…
A Scalable Whole-body Motion Transfer via Implicit Kinodynamic Motion Retargeting
Xingyu Chen, Hanyu Wu, Sikai Wu +7
Human-to-humanoid imitation learning presents a promising pathway to address the severe data scarcity bottleneck in robotics by utilizing abundant, large-scale human motion collect…
IF-MDM: Implicit Face Motion Diffusion Model for High-Fidelity Realtime Talking Head Generation
Sejong Yang, Seoung Wug Oh, Yang Zhou +1
We introduce a novel approach for high-resolution talking head generation from a single image and audio input. Prior methods using explicit face models, like 3D morphable models (3…