Object Relation Attention for Image Paragraph Captioning
Journal
35th AAAI Conference on Artificial Intelligence, AAAI 2021
Journal Volume
4A
Pages
3136-3144
Date Issued
2021
Author(s)
Abstract
Image paragraph captioning aims to automatically generate a paragraph from a given image. It is an extension of image captioning in terms of generating multiple sentences instead of a single one, and it is more challenging because paragraphs are longer, more informative, and more linguistically complicated. Because a paragraph consists of several sentences, an effective image paragraph captioning method should generate consistent sentences rather than contradictory ones. It is still an open question how to achieve this goal, and for it we propose a method to incorporate objects' spatial coherence into a language-generating model. For every two overlapping objects, the proposed method concatenates their raw visual features to create two directional pair features and learns weights optimizing those pair features as relation-aware object features for a language-generating model. Experimental results show that the proposed network extracts effective object features for image paragraph captioning and achieves promising performance against existing methods. Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved
Other Subjects
Artificial intelligence; Generating models; Image captioning; Learn+; Object-relations; Performance; Spatial coherence; Two-directional; Visual feature; Visual languages
Type
conference paper