Generating a description of an image is called image captioning. Image captioning requires
recognizing the important objects, their attributes, and their relationships in an image. It also …

Automated chart analysis has vast potential to improve the accessibility of charts for a wider
audience, eg, people with visual impairments or other disabilities, by generating captions for …

Top-down visual attention mechanisms have been used extensively in image captioning
and visual question answering (VQA) to enable deeper image understanding through fine …

Abstract A Semantic Compositional Network (SCN) is developed for image captioning, in
which semantic concepts (ie, tags) are detected from the image, and the probability of each …

We propose a novel supervised learning technique for summarizing videos by automatically
selecting keyframes or key subshots. Casting the task as a structured prediction problem …

Grounding (ie localizing) arbitrary, free-form textual phrases in visual content is a
challenging problem with many applications for human-computer interaction and image-text …

Much of the recent progress in Vision-to-Language problems has been achieved through a
combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …

Much recent progress in Vision-to-Language (V2L) problems has been achieved through a
combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …

We propose a novel attention based deep learning architecture for visual question
answering task (VQA). Given an image and an image related natural language question …

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 …