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Towards Accurate Text-based Image Captioning with Content Diversity Exploration by Xu, Guanghui; Niu, Shuaicheng; Tan, Mingkui; Luo, Yucheng; Du, Qing; Wu, Qi is a scholarly article available to read on EtoBox.

What is Towards Accurate Text-based Image Captioning with Content Diversity Exploration about?

Text-based image captioning (TextCap) which aims to read and reason images with texts is crucial for a machine to understand a detailed and complex scene environment, considering that texts are omnipresent in daily life. This task, however, is very challenging because an image often contains complex texts and visual information that is hard to be described comprehensively. Existing methods attempt to extend the traditional image captioning methods to solve this task, which focus on describing the overall scene of images by one global caption. This is infeasible because the complex text and visual information cannot be described well within one caption. To resolve this difficulty, we seek to generate multiple captions that accurately describe different parts of an image in detail. To achieve this purpose, there are three key challenges: 1) it is hard to decide which parts of the texts of images to copy or paraphrase; 2) it is non-trivial to capture the complex relationship between diverse texts in an image; 3) how to generate multiple captions with diverse content is still an open problem. To conquer these, we propose a novel Anchor-Captioner method. Specifically, we first find the

Author

Xu, Guanghui; Niu, Shuaicheng; Tan, Mingkui; Luo, Yucheng; Du, Qing; Wu, Qi

Published

2021

Language

EN