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Image caption generation with high-level image features
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AI
DOI：10.1016/j.patrec.2019.03.021.png)
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摘要
En 中文
Recently, caption generation has raised a huge interests in images and videos. However, it is challenging for the models to select proper subjects in a complex background and generate desired captions in high-level vision tasks. Inspired by recent works, we propose a novel image captioning model based on high-level image features. We combine low-level information, such as image quality, with high-level features, such as motion classification and face recognition to detect attention regions of an image. We demonstrate that our attention model produces good performance in experiments on MSCOCO, Flickr 30K, PASCL and SBU datasets. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Image captioning
Language model
Bottom-up attention mechanism
Faster R-CNN
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
8.0K
被引数:
1.6W
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