5 papers
MatchingPolicy: Correspondence-Aware Policy Enables Cross-Object In-Context Learning
Qijin She, Hanyang Yu, Zeming Li +1
In-context imitation learning enables few-shot policy generalization but struggles to maintain performance on unseen objects and novel scenarios. To address this, we introduce Matc…
Grasp, Handover, Rotate: Bimanual Object Reorientation via Compositional Diffusion and Energy-Based Optimization
Wun Lam Yeung, Wenjun Liu, Yui Cheung Yu +5
Bimanual object reorientation - picking an object, handing it over between two arms, and placing it in a desired target pose - is valuable when direct placement from the initial gr…
MaskWAM: Unifying Mask Prompting and Prediction for World-Action Models
Hanyang Yu, Haitao Lin, Jingbo Zhang +4
World Action Models (WAMs) present a promising paradigm for robotic control via video prediction. However, current WAMs suffer from fundamental spatial bottlenecks: standard text i…
Universal Features Guided Zero-Shot Category-Level Object Pose Estimation
Wentian Qu, Chenyu Meng, Heng Li +6
Object pose estimation, crucial in computer vision and robotics applications, faces challenges with the diversity of unseen categories. We propose a zero-shot method to achieve cat…
Multi-GraspLLM: A Multimodal LLM for Multi-Hand Semantic Guided Grasp Generation
Haosheng Li, Weixin Mao, Weipeng Deng +7
Multi-hand semantic grasp generation aims to generate feasible and semantically appropriate grasp poses for different robotic hands based on natural language instructions. Although…