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Computer Science > Computer Vision and Pattern Recognition

arXiv:2206.09597 (cs)
[Submitted on 20 Jun 2022 (v1), last revised 22 Jun 2022 (this version, v2)]

Title:Winning the CVPR'2022 AQTC Challenge: A Two-stage Function-centric Approach

Authors:Shiwei Wu, Weidong He, Tong Xu, Hao Wang, Enhong Chen
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Abstract: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{this https URL}.
Subjects: Computer Vision and Pattern Recognition (cs.CV); Multimedia (cs.MM)
Cite as: arXiv:2206.09597 [cs.CV]
  (or arXiv:2206.09597v2 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2206.09597

Submission history

From: Shiwei Wu [view email]
[v1] Mon, 20 Jun 2022 07:02:23 UTC (196 KB)
[v2] Wed, 22 Jun 2022 13:07:41 UTC (196 KB)
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