Apr 25, 2018 · In this paper, for answering questions about movies, we put forward a Layered Memory Network (LMN) that represents frame-level and clip-level movie content.

In this paper, we explore how to utilize movie clips and subtitles for movie question answering. We propose a Lay- ered Memory Network (LMN) to learn a layered ...

A Layered Memory Network (LMN) that represents frame-level and clip-level movie content by the Static Word Memory module and the Dynamic Subtitle Memory ...

The MovieQA dataset is a dataset for movie question answering to evaluate automatic story comprehension from both video and text.

Movie Question Answering: Remembering the Textual Cues for Layered Visual Contents. B. Wang, Y. Xu, Y. Han, and R. Hong. AAAI, page 7380-7387. AAAI Press ...

Movie Question Answering: Remembering the Textual Cues for Layered Visual Contents ... Dynamic Memory Networks for Visual and Textual Question Answering.

The LMN model ranked 1st place on MovieQA Video+Subtt-based Answering Challenge 2017 (The Joint Video and Language Understanding Workshop, ICCV 2017).

在本文中,为了回答有关电影的问题,我们提出了一个多层记忆网络(LMN),分别代表静态文字记忆模块和动态字幕记忆模块的框架级和剪辑级电影内容。特别是,我们首先从培训电影 ...

Abstract. This paper presents the Attention to Attention (A2A) rea- soning mechanism to address the challenging task of movie question an- swering (MQA).

Apr 18, 2019 · This paper proposes the progressive attention memory network (PAMN) for movie story question answering (QA). Movie story QA is challenging ...