Image captioning is one of the primary goals in computer vision which aims to automatically
generate natural descriptions for images. Intuitively, human visual system can notice some …

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 …

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

Many vision-language tasks can be reduced to the problem of sequence prediction for
natural language output. In particular, recent advances in image captioning use deep …

Automatically describing the content of an image has been attracting considerable research
attention in the multimedia field. To represent the content of an image, many approaches …

Current Image captioning (IC) methods predict textual words sequentially based on the input
visual information from the visual feature extractor and the partially generated sentence …

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 …

Image captioning aims at understanding various semantic concepts (eg, objects and
relationships) from an image and integrating them in a sentence-level description. Hence, it …

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 …

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