Keyword-driven image captioning via Context-dependent Bilateral LSTM
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2017 |
Publisher | Institute of Electrical and Electronics Engineers, Inc. |
Pages | 781-786 |
ISBN (print) | 9781509060672 |
Publication status | Published - Jul 2017 |
Publication series
Name | |
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ISSN (electronic) | 1945-788X |
Conference
Title | 2017 IEEE International Conference on Multimedia and Expo (ICME) |
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Place | Hong Kong |
Period | 10 - 14 July 2017 |
Link(s)
Abstract
Image captioning has recently received much attention. Existing approaches, however, are limited to describing images with simple contextual information, which typically generate one sentence to describe each image with only a single contextual emphasis. In this paper, we address this limitation from a user perspective with a novel approach. Given some keywords as additional inputs, the proposed method would generate various descriptions according to the provided guidance. Hence, descriptions with different Focuses can be generated for the same image. Our method is based on a new Context-dependent Bilateral Long Short-Term Memory (CDB-LSTM) model to predict a keyword-driven sentence by considering the word dependence. The word dependence is explored externally with a bilateral pipeline, and internally with a unified and joint training process. Experiments on the MS COCO dataset demonstrate that the proposed approach not only significantly outperforms the baseline method but also shows good adaptation and consistency with various keywords.
Research Area(s)
- Image Captioning, Keyword-driven, L-STM
Citation Format(s)
Keyword-driven image captioning via Context-dependent Bilateral LSTM. / Zhang, Xiaodan; He, Shengfeng; Song, Xinhang et al.
Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2017. Institute of Electrical and Electronics Engineers, Inc., 2017. p. 781-786 8019525.
Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2017. Institute of Electrical and Electronics Engineers, Inc., 2017. p. 781-786 8019525.
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review