15 research outputs found
CPARR: Category-based Proposal Analysis for Referring Relationships
The task of referring relationships is to localize subject and object
entities in an image satisfying a relationship query, which is given in the
form of \texttt{}. This requires simultaneous
localization of the subject and object entities in a specified relationship. We
introduce a simple yet effective proposal-based method for referring
relationships. Different from the existing methods such as SSAS, our method can
generate a high-resolution result while reducing its complexity and ambiguity.
Our method is composed of two modules: a category-based proposal generation
module to select the proposals related to the entities and a predicate analysis
module to score the compatibility of pairs of selected proposals. We show
state-of-the-art performance on the referring relationship task on two public
datasets: Visual Relationship Detection and Visual Genome.Comment: CVPR 2020 Workshop on Multimodal Learnin