English

Visual Semantic Relatedness Dataset for Image Captioning

Computation and Language 2023-05-02 v2 Computer Vision and Pattern Recognition

Abstract

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.

Keywords

Cite

@article{arxiv.2301.08784,
  title  = {Visual Semantic Relatedness Dataset for Image Captioning},
  author = {Ahmed Sabir and Francesc Moreno-Noguer and Lluís Padró},
  journal= {arXiv preprint arXiv:2301.08784},
  year   = {2023}
}

Comments

Project Page: bit.ly/project-page-paper

R2 v1 2026-06-28T08:16:38.678Z