Context-Aware Visual Policy Network for Sequence-Level Image Captioning-Reference-Cited by-同舟云学术

Context-Aware Visual Policy Network for Sequence-Level Image Captioning

Published:2018-10-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 26th ACM international conference on Multimedia
language:
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Author:

Liu Daqing¹,Zha Zheng-Jun¹,Zhang Hanwang²,Zhang Yongdong¹,Wu Feng¹

Affiliation:

1. University of Science and Technology of China, Hefei, China

2. Nanyang Technological University, Singapore, Singapore

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3240508.3240632

Reference44 articles.

1. Peter Anderson Xiaodong He Chris Buehler Damien Teney Mark Johnson Stephen Gould and Lei Zhang. 2017. Bottom-up and top-down attention for image captioning and VQA. arXiv preprint arXiv:1707.07998 (2017). Peter Anderson Xiaodong He Chris Buehler Damien Teney Mark Johnson Stephen Gould and Lei Zhang. 2017. Bottom-up and top-down attention for image captioning and VQA. arXiv preprint arXiv:1707.07998 (2017).

2. VQA: Visual Question Answering

3. Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. In ICLR . Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. In ICLR .

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