Affordance-centric Question-driven Task Completion for Egocentric Assistant(AQTC) is a novel task which helps AI assistant learn from instructional videos and scripts and guide the user step-by-step. In this paper, we deal with the AQTC via a two-stage Function-centric approach, which consists of Question2Function Module to ground the question with the related function and Function2Answer Module to predict the action based on the historical steps. We evaluated several possible solutions in each module and obtained significant gains compared to the given baselines. Our code is available at \url{https://github.com/starsholic/LOVEU-CVPR22-AQTC}.
翻译:Egocentic 助理(AQTC)的以问题为中心的问题驱动任务完成是一项新颖的任务,它帮助AI助理从教学视频和脚本中学习,并逐步指导用户。在本文中,我们通过以功能为中心的两阶段方法与AQTC打交道,该方法由问题2功能模块组成,以相关功能和基于历史步骤预测行动的功能2Answer模块作为问题的基础。我们评估了每个模块中的若干可能的解决方案,并取得了与给定基线相比的重大收益。我们的代码可在\url{https://github.com/starsholic/LOVEU-CVPR22-AQTC}查阅。