Visual Semantic Relatedness Dataset for Image Captioning
This provides a resource for researchers in computer vision and NLP to improve captioning, but it is incremental as it builds on existing datasets.
The paper tackles the problem of enhancing image captioning by creating a dataset that extends COCO Captions with textual scene information, enabling integration of NLP tasks like text similarity into captioning systems.
Modern image captioning system relies heavily on extracting knowledge from images to capture the concept of a static story. In this paper, we propose a textual visual context dataset for captioning, in which the publicly available dataset COCO Captions (Lin et al., 2014) has been extended with information about the scene (such as objects in the image). Since this information has a textual form, it can be used to leverage any NLP task, such as text similarity or semantic relation methods, into captioning systems, either as an end-to-end training strategy or a post-processing based approach.