Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Triple Attention Network architecture for MovieQA   Movie question answering, or MovieQA is a multimedia related task wherein one
is provided with a video, the subtitle information, a question and candidate
answers for it. The task is to predict the correct answer for the question
using the components of the multimedia - namely video/images, audio and text.
Traditionally, MovieQA is done using the image and text component of the
multimedia. In this paper, we propose a novel network with triple-attention
architecture for the inclusion of audio in the Movie QA task. This architecture
is fashioned after a traditional dual attention network focused only on video
and text. Experiments show that the inclusion of audio using the
triple-attention network results provides complementary information for Movie
QA task which is not captured by visual or textual component in the data.
Experiments with a wide range of audio features show that using such a network
can indeed improve MovieQA performance by about 7% relative to just using only
visual features.

18
The categories of this paper are: econ
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci