Visually grounded paraphrase identification via gating and phrase localization

NEUROCOMPUTING

卷:404

Article

Otani, Mayu¹  Chu, Chenhui²  Nakashima, Yuta² 

[1] CyberAgent Inc, Tokyo, Japan

[2] Osaka Univ, Inst Databil Sci, Suita, Osaka, Japan

关键词: Visual grounded paraphrases;    Gating;    Phrase localization;    Vision and language;   

DOI  :  10.1016/j.neucom.2020.04.066

来源: Elsevier

【 摘 要 】

Visually grounded paraphrases (VGPs) describe the same visual concept but in different wording. Previous studies have developed models to identify VGPs from language and visual features. In these existing methods, language and visual features are simply fused. However, our detailed analysis indicates that VGPs with different lexical similarities require different weights on language and visual features to maximize identification performance. This motivates us to propose a gated neural network model to adaptively control the weights. In addition, because VGP identification is closely related to phrase localization, we also propose a way to explicitly incorporate phrase-object correspondences. From our evaluation in detail, we confirmed our model outperforms the state-of-the-art model. (C) 2020 Elsevier B.V. All rights reserved.

【 授权许可】

Free