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Creativity: Generating Diverse Questions Using Variational Autoencoders
AbstractGenerating diverse questions for given images is an important task for computational education, entertainment and AI assistants. Different from many conventional prediction techniques is the need for algorithms to generate a diverse set of plausible questions, which we refer to as "creativity". In this paper we propose a creative algorithm for visual question generation which combines the advantages of variational autoencoders with long short-term memory networks. We demonstrate that our framework is able to generate a large set of varying questions given a single input image.
Related Material
[pdf] [supp] [arXiv] [poster][bibtex]@InProceedings{Jain_2017_CVPR,
author = {Jain, Unnat and Zhang, Ziyu and Schwing, Alexander G.},
title = {Creativity: Generating Diverse Questions Using Variational Autoencoders},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}
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