6 citations · 8 across the 5 of their papers we have counts for
5 papers
Ag2Manip: Learning Novel Manipulation Skills with Agent-Agnostic Visual and Action Representations
Puhao Li, Tengyu Liu, Yuyang Li +6
Autonomous robotic systems capable of learning novel manipulation tasks are poised to transform industries from manufacturing to service automation. However, modern methods (e.g.,…
Move as You Say, Interact as You Can: Language-guided Human Motion Generation with Scene Affordance
Zan Wang, Yixin Chen, Baoxiong Jia +7
Despite significant advancements in text-to-motion synthesis, generating language-guided human motion within 3D environments poses substantial challenges. These challenges stem pri…
AnySkill: Learning Open-Vocabulary Physical Skill for Interactive Agents
Jieming Cui, Tengyu Liu, Nian Liu +3
Traditional approaches in physics-based motion generation, centered around imitation learning and reward shaping, often struggle to adapt to new scenarios. To tackle this limitatio…
UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy
Yinzhen Xu, Weikang Wan, Jialiang Zhang +10
In this work, we tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting. The goal is to grasp and lift up obje…
Diffusion-based Generation, Optimization, and Planning in 3D Scenes
Siyuan Huang, Zan Wang, Puhao Li +5
We introduce SceneDiffuser, a conditional generative model for 3D scene understanding. SceneDiffuser provides a unified model for solving scene-conditioned generation, optimization…