In this paper, we present an image parsing to text description (I2T) framework that generates
text descriptions of image and video content based on image understanding. The proposed …

Two of the fundamental tasks in image understanding using text are caption generation and
visual question answering (Antol et al., 2015; Xiong et al., 2016). This work presents an …

Studying natural language, and especially how people describe the world around them can
help us better understand the visual world. In turn, it can also help us in the quest to …

Despite the fact that image understanding and natural language processing constitute two
major areas of AI, there have only been a few attempts toward the integration of computer …

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 …

We present a holistic data-driven approach to image description generation, exploiting the
vast amount of (noisy) parallel image data and associated natural language descriptions …

A challenging problem in image content extraction and classification is building a system
that automatically learns high-level semantic interpretations of images. We describe a …

Relating visual information to its linguistic semantic meaning remains an open and
challenging area of research. The semantic meaning of images depends on the presence of …

The problem of describing images through natural language has gained importance in the
computer vision community. Solutions to image description have either focused on a top …

We present a system to automatically generate natural language descriptions from images.
This system consists of two parts. The first part, content planning, smooths the output of …