Attention-based Image Captioning and Evaluation Methods
Khushboo Khurana · 2021
Image captioning has attracted more and more attention in the field of artificial intelligence. It is a challenging task that involves natural language description generation by automatic visual data analysis. This involves understanding the visual contents of the image and then generating natural language sentences describing the image. A number of techniques have been proposed to solve this problem. This chapter presents a survey on deep learning-based image captioning techniques and the recent advances in this field. An exhaustive explanation of the evaluation metrics is also presented. The focus of this chapter is attention-guided methods since they have shown promising results for image caption generation. The existing evaluation methods are discussed in detail, along with examples to elaborate the mechanism behind them. Furthermore, the most used benchmark datasets – Flickr8k, Flick30k, and MS-COCO – are also described. Image captioning has applications in many areas. In this chapter, the application of image captioning on industrial images is presented.