Knowing Where to Look? Analysis on Attention of Visual Question Answering System

Wei Li, Zehuan Yuan, Xiangzhong Fang, Changhu Wang; Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2018, pp. 0-0

Abstract


AttentionmechanismshavebeenwidelyusedinVisualQuestion Answering (VQA) solutions due to their capacity to model deep cross-domain interactions. Analyzing attention maps offers us a perspective to find out limitations of current VQA systems and an opportunity to further improve them. In this paper, we select two state-of-the-art VQA approaches with attention mechanisms to study their robustness and disadvantages by visualizing and analyzing their estimated attention maps. We find that both methods are sensitive to features, and simultaneously, they perform badly for counting and multi-object related questions. We believe that the findings and analytical method will help researchers identify crucial challenges on the way to improve their own VQA systems.

Related Material


[pdf] [arXiv]
[bibtex]
@InProceedings{Li_2018_ECCV_Workshops,
author = {Li, Wei and Yuan, Zehuan and Fang, Xiangzhong and Wang, Changhu},
title = {Knowing Where to Look? Analysis on Attention of Visual Question Answering System},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV) Workshops},
month = {September},
year = {2018}
}