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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/135531

Title:	Visual Story Ordering with a Bidirectional Writer
Authors:	黃瀚萱 Huang, Hen-Hsen Lin, Wei-Rou Chen, Hsin-Hsi
Contributors:	資科系
Keywords:	Multimodal modeling;temporal information ordering;sentence ordering;visual-semantic representation
Date:	2020-06
Issue Date:	2021-06-04 14:45:27 (UTC+8)
Abstract:	This paper introduces visual story ordering, a challenging task in which images and text are ordered in a visual story jointly. We propose a neural network model based on the reader-processor-writer architecture with a self-attention mechanism. A novel bidirectional decoder is further proposed with bidirectional beam search. Experimental results show the effectiveness of the approach. The information gained from multimodal learning is presented and discussed. We also find that the proposed embedding narrows the distance between images and their corresponding story sentences, even though we do not align the two modalities explicitly. As it addresses a general issue in generative models, the proposed bidirectional inference mechanism applies to a variety of applications.
Relation:	Proceedings of the 2020 International Conference on Multimedia Retrieval (ICMR ’20), Association for Computing Machinery, pp.326-330
Data Type:	conference
DOI 連結:	https://doi.org/10.1145/3372278.3390735
DOI:	10.1145/3372278.3390735
Appears in Collections:	[資訊科學系] 會議論文

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