论文标题
赢得CVPR'2022 AQTC挑战：以功能为中心的两阶段方法
Winning the CVPR'2022 AQTC Challenge: A Two-stage Function-centric Approach
论文作者
论文摘要
Egentric Assistant（AQTC）以负担为中心的问题驱动的任务完成是一项新颖的任务，可帮助AI助手从教学视频和脚本中学习，并逐步指导用户。在本文中，我们通过以两个阶段函数为中心的方法来处理AQTC，该方法由问题2功能模块组成，以使用相关函数和功能2answer模块将问题扎根，以基于历史步骤来预测操作。我们评估了每个模块中的几种可能的解决方案，并与给定基准相比获得了显着的收益。我们的代码可在\ url {https://github.com/starsholic/loveu-cvpr22-aqtc}上找到。
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}.
