Recurrent Highway Networks with Language CNN for Image Captioning
In this paper, we propose a Recurrent Highway Network with Language CNN for image caption generation. Our network consists of three sub networks: the deep Convolutional Neural Network for image representation, the Convolutional Neural Network for language modeling, and the Multimodal Recurrent Highway Network for sequence prediction. Our proposed model can naturally exploit the hierarchical and temporal structure of history words, which are critical for image caption generation. The effectiveness of our model is validated on two datasets MS COCO and Flickr30K. Our extensive experiment results show that our method is competitive with the state of the art methods.
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