4 accepted papers
Affordance grounding focuses on predicting the specific regions of objects that are associated with the actions to be performed by robots. It plays a vital role in the fields of human-robot interaction, human-object interaction, embodied manipulation, and embodied perception. Existing models often n
Multi-task imitation learning (MTIL) has shown significant potential in robotic manipulation by enabling agents to perform various tasks using a single policy. It simplifies the policy deployment and enhances the agent
Successfully solving long-horizon manipulation tasks remains a fundamental challenge. These tasks involve extended action sequences and complex object interactions, presenting a critical gap between high-level symbolic planning and low-level continuous control. To bridge this gap, two essential capa…
3D reconstruction methods such as 3D Gaussian Splatting (3DGS), have achieved significant advancements in recent years. However, the study of articulated objects remains limited due to their geometric and dynamic complexity. We propose Splatter Joint, a novel method that models articulated objects,