  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}.
