We address personalization issues of image captioning, which have not been discussed yet
in previous research. For a query image, we aim to generate a descriptive sentence …

We address personalized image captioning, which generates a descriptive sentence for a
user's image, accounting for prior knowledge such as her active vocabulary or writing style …

Recently, much advance has been made in image captioning, and an encoder-decoder
framework has been adopted by all the state-of-the-art models. Under this framework, an …

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

Visual attention has been successfully applied in structural prediction tasks such as visual
captioning and question answering. Existing visual attention models are generally spatial …

Recent works in image captioning have shown very promising raw performance. However,
we realize that most of these encoder-decoder style networks with attention do not scale …

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 …

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 is a difficult problem for machine learning algorithms to compress huge
amounts of images into descriptive languages. The recurrent models are popularly used as …

Image captioning is a challenging problem owing to the complexity in understanding the
image content and diverse ways of describing it in natural language. Recent advances in …