将来の活動を予測するための表現学習
Learning Representations for Predicting Future Activities
環境のダイナミクスを自己教師あり学習で埋め込み表現として獲得し、複数仮説スキームで将来の活動を予測・説明文生成する手法を提案した論文。
著者: Mohammadreza Zolfaghari, Özgün Çiçek, Syed Mohsin Ali, Farzaneh Mahdisoltani, Can Zhang, Thomas Brox
分類: cs.CV, cs.AI, cs.IT, cs.RO, math.IT
原文アブストラクト
Foreseeing the future is one of the key factors of intelligence. It involves understanding of the past and current environment as well as decent experience of its possible dynamics. In this work, we address future prediction at the abstract level of activities. We propose a network module for learning embeddings of the environment's dynamics in a self-supervised way. To take the ambiguities and high variances in the future activities into account, we use a multi-hypotheses scheme that can represent multiple futures. We demonstrate the approach by classifying future activities on the Epic-Kitchens and Breakfast datasets. Moreover, we generate captions that describe the future activities
