Fast Parameter Adaptation for Few-shot Image Captioning and Visual Question Answering-Reference-Cited by-同舟云学术

Fast Parameter Adaptation for Few-shot Image Captioning and Visual Question Answering

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:

Dong Xuanyi¹,Zhu Linchao¹,Zhang De²,Yang Yi¹,Wu Fei³

Affiliation:

1. Southern University of Science and Technology & University of Technology Sydney, Sydney, Australia

2. China Electronics Technology Group Corporation, Beijing, China

3. Zhejiang University, Zhejiang, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3240508.3240527

Reference52 articles.

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2. VQA: Visual Question Answering

3. Shaojie Bai J Zico Kolter and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. arXiv preprint arXiv:1803.01271 (2018). Shaojie Bai J Zico Kolter and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. arXiv preprint arXiv:1803.01271 (2018).

4. Kyunghyun Cho Bart van Merrienboer Caglar Gulcehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk and Yoshua Bengio. 2014. Learning Phrase Representations using RNN Encoder--Decoder for Statistical Machine Translation. In EMNLP . Kyunghyun Cho Bart van Merrienboer Caglar Gulcehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk and Yoshua Bengio. 2014. Learning Phrase Representations using RNN Encoder--Decoder for Statistical Machine Translation. In EMNLP .

5. Xuanyi Dong Junshi Huang Yi Yang and Shuicheng Yan. 2017a. More Is Less: A More Complicated Network With Less Inference Complexity. In CVPR . Xuanyi Dong Junshi Huang Yi Yang and Shuicheng Yan. 2017a. More Is Less: A More Complicated Network With Less Inference Complexity. In CVPR .

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