Research Area:  Machine Learning

Abstract:

Image captioning refers to automatic generation of descriptive texts according to the visual content of images. It is a technique integrating multiple disciplines including the computer vision (CV), natural language processing (NLP) and artificial intelligence. In recent years, substantial research efforts have been devoted to generate image caption with impressive progress. To summarize the recent advances in image captioning, we present a comprehensive review on image captioning, covering both traditional methods and recent deep learning-based techniques. Specifically, we first briefly review the early traditional works based on the retrieval and template. Then deep learning-based image captioning researches are focused, which is categorized into the encoder-decoder framework, attention mechanism and training strategies on the basis of model structures and training manners for a detailed introduction. After that, we summarize the publicly available datasets, evaluation metrics and those proposed for specific requirements, and then compare the state of the art methods on the MS COCO dataset. Finally, we provide some discussions on open challenges and future research directions.

Keywords:  
Automatic Image Captioning
computer vision (CV)
natural language processing (NLP)
artificial intelligence
Deep Learning
Machine Learning

Author(s) Name:   Yue Ming; Nannan Hu; Chunxiao Fan; Fan Feng; Jiangwan Zhou; Hui Yu

Publisher name:  IEEE

DOI:  10.1109/JAS.2022.105734

Volume Information:  Volume: 9, Issue: 8, August 2022, Page(s): 1339 - 1365

Paper Link:   https://ieeexplore.ieee.org/document/9849164