Referring expression generation from images via deep learning object extraction and fuzzy graphs
Jesús Chamorro-Martínez, Nicolás Marı́n, Míriam Mengíbar-Rodríguez, Gustavo Rivas-Gervilla, Daniel Sánchez · 2021
We propose an approach to obtain referring expressions for objects in images. Segmentation and categorization is performed via deep learning, providing the basis for a graph-based representation of the context that is later enriched with fuzzy properties. Referable objects and their corresponding expressions are obtained from the graph using extraction algorithms following a classical REG approach. The proposal is more flexible and scalable than end-to-end deep learning techniques.