Image Captioning According to User's Intention and Style
Author:
Affiliation:
1. Guangxi Normal University,Guangxi Key Lab of Multi-source Information Mining & Security,Guilin,China
2. School of Computer Science, Guangxi University of Science and Technology,Liuzhou,China,545006
Funder
National Natural Science Foundation of China
Guangxi Natural Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9891857/9889787/09892956.pdf?arnumber=9892956
Reference30 articles.
1. Multi-task sequence to sequence learning;luong;ArXiv Preprint,2015
2. Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
3. At-tend to you: Personalized image captioning with context sequence memory networks;park;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2017
4. StyleNet: Generating Attractive Visual Captions with Styles
5. Engaging Image Captioning via Personality
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