Introducing Concept And Syntax Transition Networks for Image Captioning-Reference-Cited by-同舟云学术

Introducing Concept And Syntax Transition Networks for Image Captioning

Published:2016-06-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval
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Author:

Blandfort Philipp¹,Karayil Tushar¹,Borth Damian²,Dengel Andreas²

Affiliation:

1. University of Kaiserslautern, Kaiserslautern, Germany

2. German Institute of Artificial Intelligence (DFKI), Kaiserslautern, Germany

Funder

Bundesministerium für Bildung und Forschung

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2911996.2930060

Reference14 articles.

1. Large-scale visual sentiment ontology and detectors using adjective noun pairs

2. T. Chen D. Borth T. Darrell and S.-F. Chang. Deepsentibank: Visual sentiment concept classification with deep convolutional neural networks. arXiv preprint arXiv:1410.8586 2014. T. Chen D. Borth T. Darrell and S.-F. Chang. Deepsentibank: Visual sentiment concept classification with deep convolutional neural networks. arXiv preprint arXiv:1410.8586 2014.

3. X. Chen H. Fang T. Lin R. Vedantam S. Gupta P. Dollar and C. L. Zitnick. Microsoft coco captions: Data collection and evaluation server. arXiv:1504.00325 2015. X. Chen H. Fang T. Lin R. Vedantam S. Gupta P. Dollar and C. L. Zitnick. Microsoft coco captions: Data collection and evaluation server. arXiv:1504.00325 2015.

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