Scene Image Synthesis from Natural Sentences Using Hierarchical Syntactic Analysis

Synthesizing a new image from verbal information is a challenging task that has a number of applications. Most research on the issue has attempted to address this question by providing external clues, such as sketches. However, no study has been able to successfully handle various sentences for this purpose without any other information. We propose a system to synthesize scene images solely from sentences. Input sentences are expected to be complete sentences with visualizable objects. Our priorities are the analysis of sentences and the correlation of information between input sentences and visible image patches. A hierarchical syntactic parser is developed for sentence analysis, and a combination of lexical knowledge and corpus statistics is designed for word correlation. The entire system was applied to both a clip-art dataset and an actual image dataset. This application highlighted the capability of the proposed system to generate novel images as well as its ability to succinctly convey ideas.