Hierarchical Question-Image Co-Attention for Visual Question Answering: Difference between revisions
Jump to navigation
Jump to search
(Created page with "Under progress") |
(Introduction) |
||
Line 1: | Line 1: | ||
= Introduction = | |||
Visual Question Answering (VQA) is a recent problem in computer vision and | |||
natural language processing that has garnered a large amount of interest from | |||
the deep learning, computer vision, and natural language processing communities. | |||
In VQA, an algorithm needs to answer text-based questions about images in | |||
natural language as illustrated in Figure <xr="fig:vqa-overview"/>. | |||
<figure id="fig:vqa-overview"> | |||
[[File:vqa-overview.png|thumb|800px|center|Figure 1: Figure illustrates a VQA system; whereby AI System takes an image and a text-based visual question about the image as input and outputs the answer for the visual question in natural language]]. | |||
</figure> |
Revision as of 00:01, 21 November 2017
Introduction
Visual Question Answering (VQA) is a recent problem in computer vision and natural language processing that has garnered a large amount of interest from the deep learning, computer vision, and natural language processing communities. In VQA, an algorithm needs to answer text-based questions about images in natural language as illustrated in Figure <xr="fig:vqa-overview"/>.
<figure id="fig:vqa-overview">
.
</figure>