3 accepted papers
Generating realistic hand-object interactions (HOI) videos is a significant challenge due to the difficulty of modeling physical constraints (e.g., contact and occlusion between hands and manipulated objects). Current methods utilize HOI representation as an auxiliary generative objective to guide v
Deep reinforcement learning (DRL) typically requires reinitializing training for new tasks, limiting its generalization due to isolated knowledge transfer. Meta-reinforcement learning (Meta-RL) addresses this by enabling rapid adaptation through prior task experiences, yet existing gradient-based me
Meta-Reinforcement Learning (Meta-RL) is a machine learning paradigm aimed at learning reinforcement learning policies that can quickly adapt to unseen tasks with few-shot data. Nevertheless, applying Meta-RL to real-world applications faces challenges due to the cost of data acquisition. To address…