Picture What you Read
This work addresses text-to-image generation for applications in visualization and reading comprehension, but appears incremental as it builds on existing CNN capabilities.
The authors tackled the problem of generating realistic images from text descriptions using Convolutional Neural Networks (CNNs), demonstrating the model's capacity to produce representative images through various experiments.
Visualization refers to our ability to create an image in our head based on the text we read or the words we hear. It is one of the many skills that makes reading comprehension possible. Convolutional Neural Networks (CNN) are an excellent tool for recognizing and classifying text documents. In addition, it can generate images conditioned on natural language. In this work, we utilize CNNs capabilities to generate realistic images representative of the text illustrating the semantic concept. We conducted various experiments to highlight the capacity of the proposed model to generate representative images of the text descriptions used as input to the proposed model.