Self-attention (SA) network has shown profound value in image captioning. In this paper, we
improve SA from two aspects to promote the performance of image captioning. First, we …

Abstract Interest in Artificial Intelligence (AI) and its applications has seen unprecedented
growth in the last few years. This success can be partly attributed to the advancements made …

Image captioning is a challenging task, ie, given an image machine automatically generates
natural language that matches its semantic content and has attracted much attention in …

Image captioning generates descriptions in a natural language for a given image. Due to its
great potential for a wide range of applications, many deep learning based-methods have …

Medical image report generation (MeIRG) aims at generating associated diagnosis
descriptions with natural language sentences from medical images, which is essential in the …

Unpaired Image Captioning (UIC) has been developed to learn image descriptions from
unaligned vision-language sample pairs. Existing works usually tackle this task using …

Attention mechanisms have been extensively adopted in vision and language tasks such as
image captioning. It encourages a captioning model to dynamically ground appropriate …

The task of image difference captioning aims at locating changed objects in similar image
pairs and describing the difference with natural language. The key challenges of this task …

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 …

The video captioning task aims to describe video content using several natural-language
sentences. Although one-step encoder-decoder models have achieved promising progress …