Exploiting Cross-Modal Prediction and Relation Consistency for Semisupervised Image Captioning-Reference-Cited by-同舟云学术

Exploiting Cross-Modal Prediction and Relation Consistency for Semisupervised Image Captioning

Published:2022 Issue: Volume: Page:1-13
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Yang Yang¹^ORCID,Wei Hongchen²,Zhu Hengshu³,Yu Dianhai³,Xiong Hui⁴,Yang Jian²^ORCID

Affiliation:

1. School of Computer Science and Engineering, Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, and Jiangsu Key Laboratory of Image and Video Understanding for Social Security, Nanjing University of Science and Technology, Nanjing, China

2. School of Computer Science and Engineering, PCA Lab, Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, and Jiangsu Key Laboratory of Image and Video Understanding for Social Security, Nanjing University of Science and Technology, Nanjing, China

3. Baidu Inc, Beijing, China

4. Management Science and Information Systems Department, Rutgers Business School, Rutgers University, Newark, NJ, USA

Funder

NSFC

Natural Science Foundation of Jiangsu Province of China

Jiangsu Shuangchuang (Mass Innovation and Entrepreneurship) Talent Program

Young Elite Scientists Sponsorship Program by CAST

CCF-Baidu Open Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Information Systems,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221036/6352949/09843903.pdf?arnumber=9843903

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