Visual attention has been successfully applied in image captioning to selectively incorporate
the most relevant areas to the language generation procedure. However, the attention in …

Attribute-based approaches and attention-based approaches have been proven to be
effective in image captioning. However, most attribute-based approaches simply predict …

Most existing attention-based methods on image captioning focus on the current word and
visual information in one time step and generate the next word, without considering the …

Image captioning attempts to generate a sentence composed of several linguistic words,
which are used to describe objects, attributes, and interactions in an image, denoted as …

Generating natural sentences from images is a fundamental learning task for visual-
semantic understanding in multimedia. In this paper, we propose to apply dual attention on …

Attention mechanisms are now widely used in image captioning models. However, most
attention models only focus on visual features. When generating syntax related words, little …

Image captioning aims to describe the content of an image with a complete and natural
sentence. Recently, the image captioning methods with encoder-decoder architecture has …

Attention mechanism has made great progress in image captioning, where semantic words
or local regions are selectively embedded into the language model. However, current …

The existing attention models of image captioning typically extract only word-level attention
information, ie, the attention mechanism extracts local attention information from the image …

Image Captioning, which automatically describes an image with natural language, is
regarded as a fundamental challenge in computer vision. In recent years, significant …