  Language and vision are processed as two different modal in current work for
image captioning. However, recent work on Super Characters method shows the
effectiveness of two-dimensional word embedding, which converts text
classification problem into image classification problem. In this paper, we
propose the SuperCaptioning method, which borrows the idea of two-dimensional
word embedding from Super Characters method, and processes the information of
language and vision together in one single CNN model. The experimental results
on Flickr30k data shows the proposed method gives high quality image captions.
An interactive demo is ready to show at the workshop.
