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Image caption generation with high-level image features
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DOI：10.1016/j.patrec.2019.03.021.png)
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Abstract
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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.
Keywords:
Image captioning
Language model
Bottom-up attention mechanism
Faster R-CNN
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